Nutritional status and its associated factors among adult People living with HIV: A Multi-facility level Study

Nutritional status and its associated factors among adult People living with HIV: A Multi-facility level Study | 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 Nutritional status and its associated factors among adult People living with HIV: A Multi-facility level Study Amare Admasu, Eskinder Wolka, Amene Abebe This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8484488/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background: Malnutrition remains a major public health concern among adults living with HIV (PLHIV), yet evidence on its magnitude and its associated factors is limited in the study settings. Objective: To assess the nutritional status and associated factors among adults living with HIV. Methods: A multi-facility cross-sectional study was conducted across four hospitals and four health centers selected using a lottery method. A total sample of 927 adults on antiretroviral therapy (ART) was proportionally allocated based on currently on antiretroviral therapy (COA) case load. Data were collected through face-to-face interviews using systematic random sampling. Nutritional status was classified using Body Mass Index (BMI): underweight (<18.5 kg/m²), normal (18.5–24.9 kg/m²), and overweight (≥25 kg/m²). Analyses were performed using STATA version 17. Multinomial logistic regression identified predictors of nutritional status at a 95% confidence level with p < 0.05. Results: The prevalence of malnutrition was 43.75%, including 19.54% (95% CI: 16.98–22.11%) underweight and 24.21% (95% CI: 21.44–26.98%) overweight. Underweight was significantly associated with nutritional screening (ARR = 2.11, 95% CI: 1.35–3.31), secondary education (ARR = 2.95, 1.33–6.56), lack of fruit intake (ARR = 1.96, 1.26–3.04), physical inactivity (ARR = 2.12, 1.22–3.69), tobacco smoking (ARR = 3.32, 1.25–8.79), depression (ARR = 8.26, 3.16–21.60), skin infection (ARR = 1.79, 1.00–3.21), and low CD4 count (<200: ARR = 4.18, 1.56–11.16; 201–350: ARR = 1.94, 1.10–3.39). Reduced risk of underweight was observed among participants who were sons/daughters or homeless (ARR = 0.24, 0.09–0.59) and those who chewed khat (ARR = 0.19, 0.07–0.49). Overweight was less likely among participants with vocational/diploma education (ARR = 0.49, 0.24–0.99), middle wealth status (ARR = 0.44, 0.25–0.80), reduced appetite (ARR = 0.29, 0.13–0.66), ≥30 minutes of daily physical activity (ARR = 0.54, 0.35–0.83), and khat chewers (ARR = 0.25, 0.11–0.53). Overweight was more likely among those relying on a single food group (ARR = 2.64, 1.76–3.96), lacking fruit intake (ARR = 1.48, 1.00–2.19), smoking tobacco (ARR = 2.48, 1.09–5.65), and having a skin infection (ARR = 2.07, 1.25–3.44). Additionally, each one-unit increase in family size increased the risk of overweight by 24% (ARR = 1.24, 1.10–1.40). Conclusion: Malnutrition among PLHIV presents a dual burden of underweight and overweight influenced by socio-demographic, dietary, behavioral, and clinical factors. Strengthening routine nutritional screening, delivering targeted dietary counseling, promoting physical activity, addressing mental health concerns, and improving management of infections are essential to enhance treatment outcomes and quality of life for PLHIV. Fruit intake nutritional status physical activities khat tobacco smoking Ethiopia Figures Figure 1 Figure 2 1. Backgrounds The global burden of HIV remains substantial, affecting over 0.5% of the world’s population and contributing to more than 5,000 new infections each day ( 1 ). In 2024, an estimated 40.8 million people were living with HIV, with approximately 630,000 deaths attributed to AIDS-related illnesses ( 2 ). Despite significant investments in HIV programs worldwide ( 3 ), malnutrition continues to pose a major challenge, particularly in sub-Saharan Africa ( 4 – 6 ). In Ethiopia, recurrent droughts, food insecurity, and persistent poverty further exacerbate nutritional vulnerabilities among people living with HIV (PLHIV) ( 7 – 9 ). Undernutrition among adults receiving antiretroviral therapy (ART) varies widely across regions, from 25.5% in Dilla ( 10 ) to as high as 60% in Benishangul Gumuz ( 11 ), reflecting differences in socio-economic conditions and access to health services. Nutritional status reflects the balance between dietary intake and the body’s physiological needs, supporting growth, recovery, and immune function ( 12 , 13 ). Disruption of this balance leads to malnutrition, manifested as undernutrition, micronutrient deficiency, or overweight ( 14 – 16 ). Among people living with HIV (PLHIV), malnutrition and HIV create a vicious cycle: malnutrition weakens immune function, while HIV increases nutrient requirements, reduces food intake and absorption, and alters metabolism, leading to weight loss and further immune suppression ( 17 , 18 ). Undernutrition among PLHIV remains a critical challenge in sub-Saharan Africa, with reported prevalence ranging from 10–13% in South Africa ( 6 , 17 ), 19.4% in Tanzania ( 4 ), and 13.8% in Ghana ( 5 ). In Ethiopia, undernutrition among HIV-positive adults remains high, reaching 27.4% in 2021 ( 7 , 9 , 19 ). Despite global commitments under the Sustainable Development Goals (SDGs) to end hunger and ensure universal access to nutritious food, persistent inequalities, food insecurity, and rising living costs continue to hinder progress ( 20 ). Inadequate facility capacity and shortages of nutritional supplements further constrain effective nutritional care for PLHIV ( 21 ). Poor nutrition accelerates HIV progression, impairs immunity, and reduces physical and mental well-being ( 22 ). Limited dietary diversity characterized by consumption of foods from few food groups remains widespread, with about one-third of PLHIV lacking adequate dietary knowledge and practices ( 23 – 26 ). Although nutrition counseling and education are essential for improving dietary diversity and treatment outcomes, implementation remains inconsistent, particularly in southern Ethiopia. Studies have done so far have linked malnutrition in this group to poor dietary diversity, household food insecurity, tobacco use, depression, and inadequate nutrition counseling ( 27 – 30 ). Although Ethiopia has developed national HIV and nutrition policies ( 24 , 31 – 33 ), implementation remains suboptimal, with many undernourished patients discharged without receiving standard nutritional therapy ( 25 ). Evidence on the nutritional status of PLHIV in Ethiopia is also scarce, and reported prevalence of underweight varies widely across regions and countries, particularly in sub-Saharan Africa ( 34 ). In the Wolaita Zone, where HIV prevalence is estimated at 0.4% and antiretroviral therapy (ART) coverage reaches 84.7% ( 19 ), information on the nutritional status of PLHIV and its determinants remains insufficient. The few available data are largely derived from single-facility studies. For example, a study conducted in 2017 reported an undernutrition prevalence of 26.6% among PLHIV ( 35 ), highlighting the need for more comprehensive, multi-facility investigations to better capture the regional burden. There is growing recognition that nutrition is a core component of effective HIV care. The World Health Organization has emphasized integrating nutritional support into national HIV/AIDS strategies ( 36 ). However, in Ethiopia, nutrition has not yet been fully operationalized as a central element of HIV care programs ( 37 ). Therefore, this study aimed to assess the nutritional status and identify factors associated with malnutrition among adults living with HIV in South Ethiopia. The findings are intended to inform policymakers and program implementers, strengthen integrated HIV–nutrition interventions, improve dietary counseling, and ultimately enhance treatment outcomes and quality of life among PLHIV. 2. Materials and Method Study design and period A multi-facility cross-sectional study was conducted from January 15 to March 30, 2025, to assess the nutritional status and associated factors. Study settings The study was conducted in the Wolaita Zone of southern Ethiopia, located approximately 342 km south of Addis Ababa. The zone has an estimated population of 2.8 million and is administratively divided into 23 districts (16 rural and 7 urban) and 355 kebeles ( 38 , 39 ). Wolaita zone, the political and administrative center of the region, is a hotspot for HIV transmission and in-migration. Antiretroviral therapy (ART) services are provided in 20 health facilities, including 7 public hospitals, 2 non-governmental hospitals, and 11 health centers, serving about 4,649 adults on ART. Study participants Antiretroviral therapy (ART) registers maintained at the selected health facilities were used as the sampling frame. The study population consisted of adults living with HIV who had been receiving ART for at least six months. Eligible participants were aged 18 years or older, who were taking ART for at least six months prior to the study, and were actively enrolled in ART care. Pregnant or lactating women, patients with edema, individuals who were critically ill, and those unable to communicate were excluded from the study. A multistage sampling technique was employed. First, three public hospitals, four health centers, and one non-governmental hospital were selected using a lottery method. Sample size was then proportionally allocated to each facility based on the number of adults on ART (Fig. 1). Participants were selected using systematic random sampling, with a sampling interval of four (K = n). The first participant at each facility was selected by lottery, and subsequent participants were enrolled at regular intervals. Variables Dependent variable Nutritional status, determined by Body Mass Index (BMI). Independent variables : Socio-demographic and economic factors age, sex, residence, education, occupation, income, wealth index, marital status, family size, and religion. Dietary factors meal frequency, dietary diversity, and nutrition knowledge, attitudes, and practices. Medical and immunological factors CD4 count, WHO clinical stage, ART duration and regimen, opportunistic infections, diarrhea, and anemia. Behavioral and personal factors substance use depression, stigma & discrimination, and physical activity. Schematic Presentation of Sample Drawing Figure 1: Schematic representation of sampling procedure in PLHIV, Wolaita zone, 2023. NB : PPS: - "probability proportionate to size" or PPS sampling and SRS:- systematic random sampling Sample Size and Sampling Procedure The sample size was initially calculated using a single population proportion formula: n = Z²p(1 − p)/d², based on a 25.2% prevalence of undernutrition among adults receiving ART ( 10 ), a 5% margin of error, a 95% confidence level, and a design effect of 2. After adding a 10% allowance for non-response, the minimum required sample size was 638 participants. To ensure adequate power for identifying factors associated with malnutrition, a second sample size estimation was performed using Epi Info version 7 with a double-population proportion formula. Malnutrition (underweight or overweight) was considered the outcome variable. Based on evidence from southwest Ethiopia showing that being single was associated with 2.2 times higher odds of underweight, a 1:1 case-to-control ratio, 5% significance level (two-sided), and 80% power were applied. This yielded a required sample size of 842. After accounting for a 10% non-response rate, the final sample size was set at 927 participants ( 40 ). Participants were selected using systematic random sampling with proportional allocation based on ART caseloads at each facility. Data Collection tools and procedures Data were collected through face-to-face interviews using a structured questionnaire. The instrument captured information on socio-demographic characteristics, dietary habits, household food insecurity, behavioral and personal factors, physical activity, and HIV-related clinical variables. The questionnaire was initially prepared in English, translated into Wolaitato language, and back-translated to ensure consistency. A pretest was conducted among 46 PLHIV (approximately 5% of the sample) at the ART clinic of Sodo Christian General Hospital. Based on the pretest, minor revisions were made to improve clarity and reduce interview time. These included adding items related to family relationships, revising meal frequency categories in the dietary diversity questionnaire, and reducing the total number of questions. Face validity was assessed during pretesting, and construct validity was ensured through clear operational definitions for all variables. Anthropometric measurements were taken according to World Health Organization (WHO) guidelines. Excess clothing like jacket, scarf etc was requested to remove during body weight measurement. For height measurement, participants were requested to stand erect, looking straight in the horizontal plane with feet together and knees straight. Weight was measured to the nearest 0.1 kg using a calibrated Seca digital scale, and height to the nearest 0.1 cm using a portable stadiometer ( 41 ). Household food insecurity was assessed using the Food Insecurity and Nutrition Assessment for PLHIV Tool ( 42 ). Substance use was evaluated with the WHO Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST v3.1) ( 43 ), categorizing participants as low, moderate, or high risk ( 44 ). Dietary diversity was measured using the FAO Women’s Dietary Diversity Questionnaire, adapted to local food items ( 45 ). The questionnaire was first prepared by English and then translated in to Wolaitato language. The tools were pretested in 46 PLHIV (about 5% of the study participants) at ART site of Sodo Christian general Hospital. After pretesting, relationship with family members was included, food eating frequency in dietary diversity questionnaire was changed from 5 times per day [i.e. breakfast, lunch, afternoon (snack), evening (snack) and dinner] to 4 times per day [i.e. breakfast, lunch, afternoon (snack), and dinner]. To shorten the interview time the number of questioners was reduced. Both face and construct validation of questioner was assured. face validation was assessed during pretesting and modifications were made to make the question more understandable. Construct validation was ensured by making an accurate operational definition for each variable. Study definitions One of the continuous variables in this study was age, it was categorized into three equally spaced groups: 18–34 years, 35–51 years, and ≥ 52 years. Other continuous variables, including body mass index (BMI), monthly income, family size, duration of antiretroviral therapy (ART), and dietary diversity score, were categorized using established external criteria such as World Health Organization guidelines and relevant national protocols and manuals. Nutritional status, the primary outcome variable, was assessed using BMI in accordance with the Asian BMI cut-off standards ( 46 , 47 ). Body Mass Index(BMI) was calculated as weight (kg) divided by height squared (m²) and classified as underweight (< 18.5 kg/m²), normal (18.5–24.9 kg/m²), or overweight (≥ 25 kg/m²) ( 48 ). Malnutrition : is defined as a deficiency, excess, or imbalance in the intake of energy and/or nutrients. It encompasses two major forms: undernutrition (underweight) and over nutrition, which includes overweight and obesity ( 49 ). Nutritional status Balance between nutrient intake and physiological requirements ( 12 ). Physical activity Categorized as high, moderate, or low according to WHO guidelines ( 50 ). Wealth index Constructed via principal component analysis of household assets, with internal consistency (Cronbach’s α = 0.86). Statistical and Analysis Data were collected using KoboToolbox, cleaned, and analyzed using STATA version 17. Descriptive statistics were used to summarize participants’ socio-demographic characteristics, HIV-related clinical factors, dietary diversity, household food insecurity, and nutritional status. Results were presented using frequencies, percentages, means with standard deviations, and medians with ranges, as appropriate. Normality of continuous variables was assessed using visual inspection of histograms and the Kolmogorov–Smirnov test. Variables that deviated from normal distribution, including CD4 count and duration of antiretroviral therapy (ART), were log-transformed to approximate normality. Categorical independent variables with more than two categories were converted into dummy variables, with the number of dummy variables equal to one less than the number of response categories. Reference categories were defined a priori. Assumptions of multinomial logistic regression including independence of observations, absence of multicollinearity, linearity of continuous variables with the logit, and independence of irrelevant alternatives were assessed before model fitting. Bivariate multinomial logistic regression was performed to identify candidate variables for multivariable analysis using a p-value threshold of ≤ 0.25. Variables meeting this criterion were included in the multivariable multinomial logistic regression model to identify independent predictors of nutritional status. Adjusted relative risk ratios (ARRs) with 95% confidence intervals were reported. Model fit was assessed using the variance inflation factor (found that VIF < 2), and statistical significance was declared at p < 0.05. Data Quality Assurance Data collectors and supervisors received three days of training covering study objectives, ethical considerations, interview techniques, and standardized anthropometric measurement procedures. Data collection was conducted by eight trained BSc-level data collectors under the supervision of two MSc-level nutrition professionals. All measurement instruments were calibrated daily using standard weights to ensure accuracy. Supervisors conducted daily reviews of completed questionnaires to check for completeness, consistency, and data quality. The Nutrition Care and Support Guidelines for people living with HIV (PLHIV) were strictly followed throughout the data collection process. Interviews were conducted in private settings to maintain participant confidentiality. Ethical Considerations Ethical approval was obtained from the Institutional Review Board of Wolaita Sodo University (Ref. No. WSU-IRBC/016/2024). Official permissions were also secured from the Wolaita Zonal Health Department and all participating health facilities. The study was conducted in accordance with the principles of the Declaration of Helsinki. All participants were provided with clear information about the study’s objectives, procedures, potential benefits, and minimal risks prior to participation. Participation was entirely voluntary, and participants were informed of their right to withdraw from the study at any time without any consequences. Written informed consent was obtained from all participants before enrollment. Confidentiality and anonymity were strictly maintained, no incentives were offered, and participants identified with severe malnutrition or other medical conditions were referred to appropriate nutritional or clinical services. 3. Results Socio-Demographic Characteristics and Nutritional Status Of the 927 adults living with HIV approached, 921 participated in the study, giving a response rate of 99.4%. Slightly more than half were female (53.5%), and about two-thirds (67.97%) lived in urban areas. The mean age was 42.98 years (SD ± 11.55), with most participants (57.98%) aged 35–51 years. The average monthly household income was 4,163.95 Ethiopian Birr (SD ± 3,589.66), and the mean household size was 4.46 persons (SD ± 1.62). The mean body weight and height were 59.36 kg (SD ± 12.38) and 164.58 cm (SD ± 8.17), respectively, yielding a mean BMI of 23.89 kg/m² (SD ± 4.15). Half of the participants were married (50.81%), among whom 25.43% were underweight and 23.50% overweight. Nearly half (49.09%) identified as protestant with underweight and overweight prevalence of 20.13% and 24.12%, respectively. Farmers or homemakers comprised 29.86% of the sample, of whom 21.45% were underweight and 25.09% overweight. More than two-thirds (64.17%) were heads of households, with 18.95% underweight and 24.09% overweight (Table 1 ). The wealth index, constructed using principal component analysis, demonstrated high internal consistency (Cronbach’s α = 0.856). Based on EDHS classifications, the largest proportion of participants (25.8%) fell within the middle wealth quintile, where 18.91% were underweight and 17.65% were overweight. Table 1 Socio-demographic characteristics among adult people living with human immunodeficiency virus, South Ethiopia, 2025 Variables Categories Body Mass Index Underweight # ( %) Overweight # ( %) Normal # ( %) Age in a complete years 18–34 years 48( 25.13) 43(22.51) 100(52.36) 35–51 years 101(18.91) 132(24.72) 301(56.37) 52 + years 31(15.82) 48(24.49) 117(59.69) Gender of the respondents Male 74(19.37) 88(23.04) 220(53.85) Female 106(19.67) 135(25.05) 298(55.29) Place of residence Rural 61(20.68) 79(26.78) 155(52.54) Urban 119(19.01) 144(23.00) 363(57.99) Marital status Married 119(25.43) 110(23.50) 239 (51.07) Single 17(15.60) 32(29.36) 60(55.05) Widowed 24(12.24) 55(28.06) 117 (59.69) Separated 11(18.64) 15(25.42) 33(55.93) Divorced 9(10.11) 11(12.36) 69(9.66) Relationship to the household Head 112(18.95) 143(24.20) 336(56.85) Spouse 61(25.00) 60(24.59) 123 (50.41) Son/daughter, homeless/street communities 7(8.14) 20(23.26) 59(68.60) Occupation of the participant Farmer and house wife 59(21.45) 69(25.09) 147(53.45) Government employee 14(12.96) 24(22.22) 70(64.81) Non-Government employee 15(17.05) 12(13.64) 61(69.32) Daily laborer 43(26.22) 39(23.78) 82(50.00) Merchant 37(19.47) 49(25.79) 104(54.74) Carpenter, retired, students, Solder, driver 12(12.50) 30(31.25) 54(56.25) Religion Orthodox 72(18.05) 102(25.56) 225(56.39) Protestant 91(20.13) 109(24.12) 252(55.75) Catholic, Muslim, pagans 17(24.29) 12(17.14) 41(58.57) Educational status No formal education 53(29.28) 39(21.55) 89(49.17) Primary 52(17.75) 73(24.91) 168(57.34) Secondary 53(24.77) 58(27.00) 103(48.13) Vocational and diploma 11(8.94) 22(17.89) 90(73.17) Degree and above 11(10.00) 31(28.18) 68 (61.82) Wealth index Poorest 42(32.81) 30(23.44) 56(43.75) Poorer 32(18.18) 43(24.43) 101(57.39) Middle 45(18.91) 42(17.65) 151(63.45) Rich 41(19.43) 65(30.81) 105(49.43) Richest 20(11.90) 43(25.60) 105(62.50) < Nutritional Status of Participants Both undernutrition and overweight were prevalent, demonstrating a double burden of malnutrition among PLHIV. The overall prevalence of malnutrition was 43.75%, including 19.54% (95% CI: 16.98–22.11%) undernourished, 24.00% (95% CI: 21.44–26.98%) overweight, and 56.46% (with normal BMI (Table 2 ). Table 2 Nutritional status of study participants (n = 921) N % 95% CI Underweight(BMI < 18.5) 180 19.54 16.98–22.11 Normal weight (BMI 18.5–24.9) 520 56.46 53.03–59.45 Overweight (BMI ≥ 25.0) 221 24.00 21.44–26.98 Antiretroviral therapy-related and clinical characteristics Almost half (44.8%) had received ART for ≥ 15 years, and 67.21% had disclosed their HIV status to family or caregivers. Only 5.97% had ever diagnosed as having malnutrition; nearly all received therapeutic food, with 78.18% of cases recorded in 2023. A small fraction (2.6%) experienced recurrent malnutrition. Nearly all respondents (99.9%) reported not sharing therapeutic food with family members. Approximately 5.3% experienced ART interruption, while 0.3% discontinued due to undernutrition concerns. Only 3% reported acute illness, and 5.3% had doctor-diagnosed food allergies. Nutritional Knowledge and Nutrition-Related Characteristics Nutritional knowledge was assessed using six items (Cronbach’s α = 0.80). Using PCA, responses were recoded into “adequate” (> 50%) and “inadequate” (≤ 50%) knowledge categories. Overall, 81.0% demonstrated adequate knowledge, while 19.0% had inadequate knowledge. Among those with inadequate knowledge, 32.22% were underweight and 8.07% overweight, whereas among those with adequate knowledge, 67.78% were underweight and 27.48% overweight. Undernutrition was more frequent among participants with ≥ 180 months of ART, HIV status disclosure (61.11%), absence of nutritional screening (51.11%), and inadequate dietary diversity (63.89%). Conversely, overweight was also more common among long-term ART users, those who had disclosed their HIV status (70.85%), and those never diagnosed with malnutrition (92.83%) (Table 3 ). Table 3 Cross tabulation of Nutrition Knowledge and Nutritional Characteristics among study participants (n = 921) Variables Categories BMI Underweight#(%) Overweight#(%) Normal #(%) Inadequate basic nutritional Knowledge Inadequate (≤ 50%) 58(32.22) 18(8.07) 99(19.11) Adequate (> 50%) 122(67.78) 205(27.48) 419(80.89) Duration on ART in months 7–60 30(16.67) 45(20.18) 66(12.74) 61–120 17(9.44) 25(11.21) 48(9.27) 121–180 60(33.33) 64(28.70) 153(29.54) ≥ 180 73(40.56) 89(39.91) 251(48.46) Disclosure of HIV status Yes 110(61.11) 158(70.85) 351(67.76) No 70(38.89) 65(29.15) 167(32.24) Screening for nutritional status Yes 88(48.89) 60(26.91) 144(27.80) No 92(51.11) 163(73.09) 374(72.20) Ever diagnosed as having malnutrition Yes 24(13.33) 16 (7.17) 15(2.90) No 156(86.67) 107(92.83) 503(97.10) Dietary diversity Inadequate 115(63.89) 126(56.50) 275(53.09) Adequate 65(36.11) 97(43.50) 243(46.91) Source of food groups obtained from One source 71(39.44) 135(60.54) 219(42.28) 2 + sources 109(60.56) 88(39.46) 299(57.72) Dietary allergy Yes 10(5.56) 14(6.28) 25(4.83) No 170(94.44) 209(93.72) 493(95.17) History reduced appetite Yes 29(16.11) 10(4.48) 54(10.42) No 151(83.89) 213(95.52) 464(89.58) Swallowing problem over the past 3–6 months Yes 6(3.33) 3( 1.35) 24(4.63) No 174(96.67) 220(98.65) 494(95.37) A history of psychosocial or physical disabilities likely to cause weight loss Yes 45(25.00) 21(9.42) 72(13.90) No 135(75.00) 202(90.58) 446(86.10) A history of clothes and/or jewelry that have become loose-fitting (weight loss) Yes 76(42.22) 34(15.25) 114(22.01) No 104(57.78) 189(84.75) 404(77.99) Dietary Habits Most participants (95%) recognized the importance of dietary diversity; however, barriers included lack of food availability (22%) and financial constraints (52%) (Fig. 2 ). Behavioral and personal factors Physical activity levels were generally low. Only 13.1% engaged in vigorous activity, and 90.1% were inactive or exercised fewer than three days per week. Based on standardized criteria, 5.5% were minimally active and 4.3% were classified as active. Moderate physical activity was reported by 22.3%, while 38.2% reported walking or cycling for at least 10 minutes, with 21.1% doing so three to five days per week (Table 4 ). Alcohol use was reported by 18.0% of participants, with 38.6% drinking daily. Among alcohol users, 16.3% were underweight and 23.5% overweight. Khat chewing and tobacco smoking were reported by 14.4% and 9.8%, respectively. Among smokers, 24.4% were underweight and 28.9% were overweight. Stigma or discrimination related to HIV was experienced by 25.6% of participants, among whom 26.3% were underweight and 23.7% overweight. More than half (54.7%) reported lacking social support for adequate nutrition. Depressive symptoms were reported by 20.1%, including 38.2% with mild and 6.2% with moderate-to-severe symptoms (Table 4 ). Table 4 Cross tabulation of dietary habit and behavioral factors among study participants (n = 921) Categories BMI Underweight#(%) Overweight#(%) Normal #(%) Did you eaten fruits this week Yes 94(52.22) 137(61.43) 333(64.29) No 86(47.78) 86(38.57) 185(35.71) Number of servings fruits in a days 1–2 100(55.56) 93(41.70) 209(40.35) ≥ 3 80(44.44) 130(58.30) 309(59.65) Consume vegetables Yes 87(48.33) 142(63.68) 344(66.41) No 93(51.67) 81(36.32) 174(33.59) Number of days consumed vegetables per week 1–2 days 77(42.78) 111(49.78) 300(57.92) ≥ 3 days 103(57.22) 112(50.22) 218(42.08) Number of servings vegetables in a days 1–2 servings 77(42.78) 111(49.78) 300(57.92) 3 + servings 103(57.22) 112(50.22) 218(42.08) Type of oil or fat is most often used for meal preparation in your HH Vegetable oil &/or butter 32(17.78) 38(17.04) 126(24.32) Lard or suet &/or margarine 55(30.56) 104(46.64) 213(41.12) Not use oil or fat in their meal 93(51.67) 81(36.32) 179(34.56) Engaged in Vigorous intensive activities Yes 24(19.83) 42(34.71) 55(45.45) No 156(19.50) 181(22.63) 463(57.88) Days in a week Vagarious intense activity (VIA) performed < 1500 MET(< 5 D) 5(16.67) 10(33.33) 15(50.00) ≥ 1500 MET(≥ 5 D) 16(17.58) 11(12.09) 64(70.33) No VIA 159(19.88) 202(25.25) 439(54.87) Days in a week VIA performed < 1500 MET(< 5 D) 5(16.67) 10(33.33) 15(50.00) ≥ 1500 MET(≥ 5 D) 16(17.58) 11(12.09) 64(70.33) No VIA 159(19.88) 202(25.25) 439(54.87) Time spend in VIA on a typical day 20 + minutes MIA 21(17.36) 21(17.36) 79(65.29) No MIA 159(19.88) 202(25.25) 439(54.87) Moderate intense activities Yes 40(19.51) 53(25.85) 112(54.63) No 140(19.55) 170(23.74) 406(56.70) Low intense activities Yes 67(19.03) 88(25.00) 197(55.97) No 113(19.86) 135(23.73) 321(56.41) Vigorous intensity sports Yes 7(10.45) 17(25.37) 43(64.18) No 173(20.26) 206(24.12) 475(55.62) Moderate intensity sports Yes 3(33.33) 4(44.44) 2(22.22) No 177(19.41) 219(24.01) 516(56.58) Ever drink alcohol Yes 27(16.27) 39(23.49 ) 100(60.24) No 153(20.26) 184(24.37) 418(55.36) Chewing khat Yes 14(10.53) 30(22.56) 89(66.92) No 166(21.07) 193(24.49) 429(54.44) Smoking tobacco Yes 22(24.44) 26(28.89) 42(46.67) No 158(19.01) 197(23.71) 476(57.28) Stigma and discrimination Yes 62(26.27) 56(23.73) 118(50.00) No 118 (17.23) 167(24.38) 400(58.39) Depression No 38(13.97) 63(23.16 ) 171(62.87) Minimal 45(18.75) 53(22.08) 142(59.17) Mild 65(18.47) 97(27.56) 190(53.98) Moderate and severe 32(56.14) 10(17.54) 15(26.32) Medical and immunological factors Most participants (83.6%) had CD4 counts > 350 cells/mm³, while 16.4% had ≤ 350 cells/mm³. Undernutrition was more prevalent among individuals with lower CD4 counts, whereas overweight predominated among those with higher counts. The majorities (91.1%) were classified as WHO clinical stage I, yet over one-third of participants in stage II or higher were undernourished. First-line ART was used by 93.1%, with comparable undernutrition across regimens. Comorbidities affected 18.1%, mainly hypertension, diabetes, and tuberculosis. Gastrointestinal symptoms were reported by 13.3%. Household food insecurity was common, with 58.9% reducing meal size and 17.3% unable to afford balanced diets. Factors Associated with Nutritional Status In bivariate analysis, variables with p ≤ 0.25 were entered into the multivariable multinomial regression model. Independent predictors of undernutrition included being a household head, secondary education (ARR = 2.95), prior nutritional screening (ARR = 2.11), lack of fruit consumption (ARR = 1.96), physical inactivity (ARR = 2.11), tobacco smoking (ARR = 3.32), depression (ARR = 8.26), skin infections (ARR = 1.79), and CD4 count < 350 cells/mm³. Being a son/daughter or homeless (ARR = 0.24) and khat chewing (ARR = 0.19) were protective. Predictors of overweight included larger family size (ARR = 1.24), low dietary diversity (ARR = 2.64), and no fruit intake (ARR = 1.48). Protective factors were vocational or diploma-level education (ARR = 0.49), middle wealth status (ARR = 0.44), reduced appetite (ARR = 0.29), engaging in ≥ 30 minutes of daily physical activity (ARR = 0.54), and khat chewing (ARR = 0.25). Tobacco smoking (ARR = 2.48) and skin infection (ARR = 2.07) increased the risk of overweight (Table 5 ). Table 5 Multinomial regression analysis of Factors Associated with Nutritional Status of study participants (Reference = Normal Weight). Predictor Variables Underweight Vs. Normal weighted Overweight Vs. Normal weighted CRR(95% CI) ARR(95% CI) CRR( 95% CI) ARR( 95% CI) Socio-demographic characteristics Relationship with HH Head of household(HH) 1 1 1 1 Spouse 1.48(1.023–2.16)* 1.27(0.80–2.01) 1.14( 0.79–1.65) 0.95(0.62–1.44) Son/daughter, homeless/street 0.35(0.15–0.80)* 0.24(0.09–0.59)* 0.79 (0.46–1.37) 0.64(0.35–1.18) Educational status No formal education 3.68(1.78–7.57)* 2.28(1.20–6.52) 0.96(.54- 1.69) 1.31(0.67–2.55) Primary 1.91(0.94–3.88) 1.36(0.61–3.01) 0.95(0.57–1.58) 1.35(0.76–2.40) Secondary 3.18(1.55–6.52)* 2.95(1.33–6.56)* 1.23(0.72–2.10) 1.13(0.63–2.03) Vocational and diploma 0.75(0.30–1.84) 0.61(0.23–1.63) 0.53(0.28-1.00) 0.49(0.24–0.99)* Degree and above 1 1 1 1 Family size 0.95(0.85–1.05) 0.99(0.87–1.13) 1.15(1.04–1.28)* 1.24(1.10–1.40)* Wealth index Poorest 3.93(2.11–7.34)* 1.71(0.77–3.78) 1.30(0.74–2.30) 0.69(0.34–1.41) Poorer 1.66(0.89–3.09) 1.24(0.59–2.28) 1.03(0.62–1.71) 0.57(0.30–1.05) Middle 1.56( 0.873-2.80) 1.06(0.53–2.10) 0.67(0.41–1.11) 0.44(0.25–0.80)* Rich 2.05(1.12–3.73)* 1.45(0.73–2.87)* 1.51(0.94–2.42) 1.19(0.70–2.02) Richest 1 1 1 1 Nutritional and ART related factors Nutritional screening Yes 2.48(1.75–3.52)* 2.11(1.35–3.31)* 0.95(0.67–1.36) 0.85(0.56–1.31) No 1 1 1 1 Dietary diversity Inadequate or ( 1 – 3 ) food groups 1.56(1.10–2.21)* 1.32(0.88–1.98) 1.14(0.83–1.57) 1.09(0.75–1.58) Adequate 1 1 1 1 Food source One source 0.88(0.62–1.25) 0.68(0.43–1.06) 2.09(1.52–2.88)* 2.64(1.76–3.96)* 2 + sources 1 1 1 1 History of reduced appetite Yes 1.65(1.01–2.68)* 0.71(0.36–1.40) 0.40(0.20–0.80)* 0.29(0.13–0.66)* No 1 1 1 1 Dietary habit Eaten fruits in a week Yes 1 1 1 1 No 1.64( 1.16–2.32)* 1.96(1.26–3.04)* 1.12(0.81–1.56) 1.48(1.00-2.19)* Physical activity Time spend in MIA on a typical day 30 + minutes MIA 1 1 1 1 No MIA 1.89(1.17–3.05)* 2.12(1.22–3.69)* 0.74(.51-1.05) 0.54(0.35–0.83)* Personal and behavioral factors Chewing khat Yes 0.40(0.22–0.73)* 0.19(0.07–0.49)* 0.74(0.47–1.17) 0.25(0.11–0.53)* No 1 1 1 1 Smoking tobacco Yes 1.57( .91-2.72) 3.32(1.25–8.79)* 1.49(0.89–2.50) 2.48(1.09–5.65)* No 1 1 1 1 Stigma and discrimination Yes 0.56( 0.2–0.94)* 1.33(0.82–2.18) 0.87(-0.23-0.49) 1.22(0.78–1.92) No 1 1 1 1 Depression No 1 1 1 1 Minimal 0.35(-.13-0.84) 1.60(0.91–2.80) 0.01(-.41-0.44) 0.87(0.53–1.41) Mild 0.43(− .018-0.88) 1.68(0.96–2.91) 0.32(-.05-0.70) 1.23(0.77–1.96) Moderate & severe 2.26(1.55–2.96)* 8.26(3.16–21.60)* 0.59( -0.25-1.44) 2.74(0.95–7.91) Medical and immunological properties Skin change Yes 1.11(.70-1.77) 1.79(1.00-3.21)* 1.76(1.19–2.62)* 2.07(1.25–3.44)* No Ref. 1 1 1 CD4 count 350 1 1 1 1 BN: MIA-Moderate Intense Activity, ARR-Adjusted relative risk, CRR-Crude relative risk, Vs-versus, CI-Confidence Interval, *-P-value < 0.05 4. Discussion This study demonstrates a substantial double burden of malnutrition among adults living with HIV (PLHIV) in South Ethiopia, with both underweight and overweight remaining highly prevalent. Nearly two in five participants (43.75%) were malnourished, comprising 19.54% underweight and 24.21% overweight, highlighting the coexistence of nutritional deficiency and excess within the same population. This overall burden is comparable to findings from Ghana (42%) ( 5 ) but exceeds reports from South Africa (39%) ( 17 ), underscoring persistent nutritional vulnerability among PLHIV in low-resource settings. The prevalence of underweight observed in this study was lower than reports from several Ethiopian settings (26.3–37.2%) ( 10 , 51 , 52 ) but higher than estimates from Kenya (8%) ( 53 ). It closely aligns with findings from Nepal (18.3%) ( 54 ) and Tanzania (19.4%) ( 4 ), and falls within the pooled estimate for sub-Saharan Africa (23.7%) ( 55 ). Variations across studies may reflect differences in ART coverage, socioeconomic conditions, food security, and access to nutrition services. Conversely, overweight was more prevalent than underweight, mirroring patterns reported in South Africa (26%) ( 17 ), but exceeding national Ethiopian estimates (9.6–21%) ( 56 , 57 ). Although lower than levels reported in Zimbabwe, Cameroon, and Uganda ( 58 – 60 ), the observed prevalence suggests a nutrition transition among PLHIV, potentially driven by urbanization, dietary shifts toward energy-dense foods, and sociocultural norms favoring higher body weight. Socio-demographic factors played a significant role in shaping nutritional outcomes. Participants who were sons or daughters within households or homeless community members had markedly lower odds of underweight, consistent with findings from Addis Ababa ( 57 ). This may reflect shared household resources and informal social support mechanisms that buffer food insecurity. In contrast, secondary education was associated with increased odds of underweight, aligning with evidence from Ethiopia and Bangladesh ( 61 , 62 ). This counterintuitive association may reflect disparities in employment opportunities, income stability, or rural–urban differences in food access and lifestyle, emphasizing that education alone does not guarantee nutritional adequacy. This may reflect the social and economic support available within shared or extended households. Participants with secondary education were nearly three times more likely to be underweight (ARR = 2.78, 95% CI: 1.25–6.16), supporting evidence from Ethiopia ( 62 , 63 ) and Bangladesh ( 61 ) that education influences health literacy, income, and diet. Differences from other Ethiopian studies ( 57 ) could result from urban–rural variation and ART program support. The association between nutritional screening and underweight likely reflects reverse causation, whereby individuals are screened after clinical suspicion of malnutrition rather than screening preventing its occurrence ( 64 ). Similarly, limited dietary diversity and lack of fruit intake were strongly associated with underweight, reinforcing evidence that monotonous diets dominated by staple foods may provide sufficient energy but fail to meet micronutrient needs critical for immune function among PLHIV ( 65 , 66 ). Behavioral and psychosocial factors emerged as important determinants. Physical inactivity significantly increased the risk of underweight, consistent with studies from Ethiopia, Korea, and China ( 67 – 69 ). Regular physical activity supports lean body mass, appetite regulation, and immune competence, while inactivity may accelerate wasting in chronic illness ( 70 , 71 ). Tobacco smoking showed a strong association with underweight, corroborating findings from Ethiopia, Nepal, and South Africa ( 54 , 65 , 72 ), likely due to appetite suppression and increased metabolic demand. Depression was one of the strongest predictors of underweight, with affected individuals exhibiting markedly higher risk, consistent with evidence from Ethiopia, the Philippines, and Nigeria ( 73 – 75 ). This underscores the critical interplay between mental health and nutritional status in HIV care. Clinical factors further influenced nutritional outcomes. Skin infections and low CD4 counts were strongly associated with underweight, reflecting the bidirectional relationship between infection, immune suppression, and nutritional depletion ( 55 , 76 , 77 ). These findings reinforce the importance of early infection management and immunological monitoring to prevent nutritional decline. Regarding overweight, vocational or diploma-level education and middle wealth status were protective, consistent with studies from Ethiopia, Nigeria, and Zimbabwe ( 6 , 65 , 78 ). In contrast, poor dietary diversity and lack of fruit intake increased overweight risk, suggesting reliance on energy-dense but nutrient-poor diets ( 65 , 79 , 80 ). Regular physical activity reduced the likelihood of overweight, in agreement with prior evidence ( 56 , 81 , 82 ). Although khat chewing was inversely associated with overweight, its known adverse health effects warrant caution in interpretation ( 83 ). The association between skin infections and overweight observed in this study aligns with findings from Namibia and Uganda ( 59 , 84 ), and may reflect inflammatory or treatment-related metabolic changes. This study highlights the strong influence of socio-economic, behavioral, and clinical factors on the nutritional status of adults living with HIV. Underweight was more common among individuals with lower education, dependent household roles, lower wealth status, depression, skin infections, and low CD4 counts, reflecting compounded social and immunological vulnerability. Both underweight and overweight were more prevalent among economically disadvantaged participants, underscoring the dual burden of malnutrition. Reliance on single food sources and physical inactivity increased the likelihood of unhealthy weight outcomes, while dietary diversity and regular physical activity were protective. Tobacco smoking elevated the risk of malnutrition, whereas khat chewing was associated with lower odds. These findings emphasize the need for integrated, nutrition-sensitive HIV care addressing social, behavioral, and clinical determinants. 5. Conclusion This study revealed a substantial burden of malnutrition among adults living with HIV in South Ethiopia, with both underweight and overweight emerging as significant public health concerns. The simultaneous presence of these conditions reflects an ongoing nutritional transition within this population. Underweight was strongly associated with inadequate dietary practices, physical inactivity, tobacco use, depression, skin infections, and low CD4 counts. Nutritional screening and secondary education were also linked to increased underweight risk, while being a son or daughter within a homeless household and khat chewing showed reduced likelihood associations. Overweight was less common among participants with vocational or diploma education, those in the middle wealth category, individuals reporting reduced appetite, those engaging in daily physical activity, and khat chewers. In contrast, low dietary diversity, lack of fruit intake, tobacco smoking, skin infections, and larger family size significantly increased the likelihood of overweight. Addressing this dual burden of malnutrition requires coordinated action. Policy efforts should prioritize nutrition-sensitive HIV programs, ensure consistent access to food and micronutrient supplements, and strengthen community-based support systems. Enhancing Multi-Sectoral collaboration between health, agriculture, and social protection sectors is essential to improve nutritional outcomes, support treatment adherence, and ultimately enhance the quality of life of people living with HIV. Abbreviations ART, Antiretroviral Therapy; COA, Currently On ART; HC, Health Center; PH, Primary Hospital; PLHIV, People living with HIV/AIDS; LMIC, Low and Middle-Income Countries; WSUCSH, Wolaita Sodo University Comprehensive Specialized Hospital. Declarations Availability of data and materials All data supporting the findings of this study are available within the paper and its Supplementary Information. Acknowledgments I would like to express my gratitude to Wolaita Sodo University College of Medicine and Health Science for allowing me to develop this thesis. I am grateful to the Health Office of the Wolaita Sodo Health Administration Zone for providing us with the necessary information essential for the accomplishment of the research work. Finally, I express my appreciation to the study participants, data collectors, and everyone who assisted in completing the research. Their contributions in translation to the local language and encouragement are highly appreciated. Consent to participate declaration This study was conducted in full accordance with the ethical principles outlined in the Declaration of Helsinki. Ethical clearance was taken from Institutional Review Board (IRB) of Wolaita Sodo University: Ref. No. WSU-IRBC/016/2024. All procedures involving human participants were reviewed and approved by IRB. Prior to enrollment, participants were provided with full information about the study’s purpose, procedures, potential benefits, and minimal risks. They were also informed of their unconditional right to decline participation or withdraw at any stage without penalty or effect on the services they receive. Confidentiality and privacy were maintained thoroughly. Consent for Publication Not applicable Competing Interests The authors declare that they have no competing interest. Author Contributions A.A: Conceptualization, writing – original draft preparation, data curation, formal analysis, investigation, methodology, project administration, resources, software. EW: Methodology, project administration, resources, software, supervision, validation, visualization, writing – review & editing. AA: Methodology, project administration, resources, software, supervision, validation, visualization, writing review & editing. All authors have read and approved the final version submitted. Funding Information This is a self-funded research project with technical support from Wolaita Sodo University Collage of Health Science and Medicine. 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Underweight and Its Predictors Among Patients on Anti Retroviral Therapy at Selected Health Facilities of Addis Ababa, Ethiopia, 2020. available at https://www.dovepress.com/terms: . DovePress. 2021;13:99–106. Bleasel JM, Heron JE, Shamu T, Chimbetete C, Dahwa R, Gracey DM. Body mass index and noninfectious comorbidity in HIV-positive patients commencing antiretroviral therapy in Zimbabwe. HIV Med. 2020;21(10):674–9. Nalugga EA, Laker E, Nabaggala MS, Ddungu A, Batte C, Piloya T, et al. Prevalence of overweight and obesity and associated factors among people living with HIV attending a tertiary care clinic in Uganda. BMC Nutr. 2022;8(1):107. Nkanjo BM-F, Nicholas T, Ojong EW. Prevalence of Malnutrition and Associated Factors among HIV Seropositive Adults on Antiretroviral Therapy at the Regional Hospital, Buea, Cameroon. Int J Trop Disease Health. 2024;45(6):70–82. Biswas T, Garnett SP, Pervin S, Rawal LB. The prevalence of underweight, overweight and obesity in Bangladeshi adults: Data from a national survey. PLoS ONE. 2017;12(5):e0177395. Nigussie F, Sahlu D, Gizaw S. Undernutrition and Associated Factors Among Young Patients on Anti-retroviral Therapy in North Shoa, Oromia, Etiopia, 2022. A Facility-Based Cross-sectional Study. Health Sci (IJMRHS). 2023;12(7):16–27. Ayele G, Tessema B, Amsalu A, Ferede G, Yismaw G. Prevalence and associated factors of treatment failure among HIV/AIDS patients on HAART attending University of Gondar Referral Hospital Northwest Ethiopia. BMC Immunol. 2018;19(1):37. Assefa MG, Deksisa A, Abdo M, Alemayehu OT, Daka DW. Predictors of underweight among adult patients receiving antiretroviral therapy in Bishoftu general hospital, central Ethiopia: Case-control study. PLoS ONE. 2023;18(9):e0291602. Shallangwa MM, Dibal NI, Bhandari M, Musa SS, Bello HM. Malnutrition and its associated factors among people living with HIV/AIDS (PLHIV) in resource limited settings: A single-centred study. Clin Epidemiol Global Health. 2023;24:101423. Teklehaimanot AN, Belachew T, Gudina EK, Getnet M, Amdisa D, Dadi LS. Behavioral Intention towards Dietary Diversity among Adult People Living with HIV in Public Hospitals in Southwest Ethiopia Using Theory of Planned Behavior—An Explanatory Study. Challenges. 2021;12(2):18. Qin X-M, Allan R, Park J-Y, Kim S-H, Joo C-H. Impact of exercise training and diet therapy on the physical fitness, quality of life, and immune response of people living with HIV/AIDS: a randomized controlled trial. BMC Public Health. 2024;24(1):730. Tegene Y, Mengesha S, van der Starre C, Lako S, Toma A, Spigt M. Physical activity level and associated factors among adult HIV patients in Ethiopia. BMC Infect Dis. 2022;22(1):123. Zou Y, Sun P, Zhang Y, Li Y. Physical Activities and Associated Factors Among HIV/AIDS Patients: A Questionnaire Survey. DovePress: Patient Preference Adherence. 2022;16:1703–17112. Patient Prefer Adherence. https://doi.org/10.2147/PPA.S360517. Enichen E, Adams RB, Demmig-Adams B. Physical Activity as an Adjunct Treatment for People Living with HIV? Am J Lifestyle Med. 2023;17(4):502–17. Fathima S, Madhu A, Udaya Kumar M, Dhingra V, Kumar S, Singh N. Nutritional Aspects of People Living with HIV (PLHIV) Amidst COVID-19 Pandemic: an Insight. Curr Pharmacol Rep. 2022;8(5):350–64. Weldehaweria NB, Abreha EH, Weldu MG, Misgina KH. Psychosocial correlates of nutritional status among people living with HIV on antiretroviral therapy: A matched case-control study in Central zone of Tigray, Northern Ethiopia. PLoS ONE. 2017;12(3):e0174082. Adedeji WA, Ma Q, Raji AM, Cha R, Rasaki OM, Hutson A, et al. Prevalence of depression among people living with HIV in rural hospitals in South-Western Nigeria-Association with clinico-demographic factors. AIDS Res Therapy. 2023;20(1):89. Elsayed H, O'Connor C, Leyritana K, Salvana E, Cox SE. Depression, Nutrition, and Adherence to Antiretroviral Therapy in Men Who Have Sex With Men in Manila, Philippines. Front public health. 2021;9:644438. Kalil FS, Kabeta T, Jarso H, Hasen M, Ahmed J, Kabeta S. Determinants of undernutrition among adult people on antiretroviral therapy in Goba Hospital, Southeast Ethiopia: A case–control study. DovePress. 2020;12:1–15. http://doi.org/10.2147/NDS.S276311 . Shifera N, Yosef T, Matiyas R, Kassie A, Assefa A, Molla A. Undernutrition and Associated Risk Factors among Adult HIV/AIDS Patients Attending Antiretroviral Therapy at Public Hospitals of Bench Sheko Zone, Southwest Ethiopia. DOI: 10.1177/23259582221079154. J Int Association Providers AIDS Care (JIAPAC). 2022;21:1–10. Kalinjuma AV, Hussey H, Mollel GJ, Letang E, Battegay M, Glass TR, et al. Body mass index trends and its impact of under and overweight on outcome among PLHIV on antiretroviral treatment in rural Tanzania: A prospective cohort study. PLoS ONE. 2023;18(8):e0290445. Nigusso FT, Mavhandu-Mudzusi AH. High magnitude of food insecurity and malnutrition among people living with HIV/AIDS in Ethiopia: A call for integration of food and nutrition security with HIV treatment and care Programme. Nutr Health. 2021;27(2):141–50. Hema A, Poda A, Zoungrana J, Tougouma JB, Meda C, Kamoulé E et al. Body mass index trends and overweight/obesity risk among patients initiating antiretroviral therapy in Bobo-Dioulasso Day Hospital, Burkina Faso: a cohort study from 2002 to 2019. PAMJ Clin Med. 2022;9(28). Ibrahim S, Demie TG, Gelata T, Ahmed S, Bekele GG. Underweight and its associated factors among reproductive age women on antiretroviral therapy in selected public health facilities of Arsi Zone, South East Ethiopia. Clin Epidemiol Global Health. 2025;32:101953. Gilberti G, Tiecco G, Marconi S, Marullo M, Zanini B, Quiros-Roldan E. Weight gain, obesity, and the impact of lifestyle factors among people living with HIV: A systematic review. Obes reviews: official J Int Association Study Obes. 2025;26(7):e13908. Anikpe JN, Chukwu AJ, Edem EN, Elahmar AAE, Sinha S, Arome D. Effect of anthropometric and sociodemographic variables on physical activity levels of people living with human immunodeficiency virus/acquired immunodeficiency syndrome on highly active antiretroviral therapy. Tzu chi Med J. 2023;35(2):200–4. Oumer A. Khat consumption and undernutrition among adult population in Ethiopia: A systematic review and meta-analysis. PLoS ONE. 2024;19(4):e0299538. Draganescu M, Baroiu L, Iancu A, Dumitru C, Radaschin D, Polea ED, et al. Perspectives on skin disorder diagnosis among people living with HIV in southeastern Romania. Experimental Therapeutic Med. 2021;21(1):97. Additional Declarations No competing interests reported. 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04:35:32","extension":"html","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":244133,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8484488/v1/5465672c275bbb5b73764cda.html"},{"id":100750631,"identity":"c1ff0061-b119-4056-8002-062d484575a7","added_by":"auto","created_at":"2026-01-21 04:35:31","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":100226,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of sampling procedure in PLHIV, Wolaita zone, 2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNB\u003c/strong\u003e: \u003cem\u003ePPS: - \"probability proportionate to size\" or PPS sampling and SRS:- systematic random sampling\u003c/em\u003e\u003c/p\u003e","description":"","filename":"groupimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8484488/v1/95ed27909f70c7ce305da5ec.jpeg"},{"id":100750646,"identity":"2677b324-0916-4aec-9578-60bc40596c79","added_by":"auto","created_at":"2026-01-21 04:35:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eProportions of reasons for not eating diversified diet.\u003c/p\u003e","description":"","filename":"placeholderimage.png","url":"https://assets-eu.researchsquare.com/files/rs-8484488/v1/ab92e5e16398bbefd1eb93e3.png"},{"id":100804062,"identity":"3bc620d8-cc99-4249-9cf4-f84c309c2d36","added_by":"auto","created_at":"2026-01-21 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04:35:34","extension":"xls","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1503744,"visible":true,"origin":"","legend":"","description":"","filename":"DatasetusedforAnalysis1.xls","url":"https://assets-eu.researchsquare.com/files/rs-8484488/v1/e66ca7b150dd66880a72d810.xls"}],"financialInterests":"No competing interests reported.","formattedTitle":"Nutritional status and its associated factors among adult People living with HIV: A Multi-facility level Study","fulltext":[{"header":"1. Backgrounds","content":"\u003cp\u003eThe global burden of HIV remains substantial, affecting over 0.5% of the world\u0026rsquo;s population and contributing to more than 5,000 new infections each day (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In 2024, an estimated 40.8\u0026nbsp;million people were living with HIV, with approximately 630,000 deaths attributed to AIDS-related illnesses (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Despite significant investments in HIV programs worldwide (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), malnutrition continues to pose a major challenge, particularly in sub-Saharan Africa (\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In Ethiopia, recurrent droughts, food insecurity, and persistent poverty further exacerbate nutritional vulnerabilities among people living with HIV (PLHIV) (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Undernutrition among adults receiving antiretroviral therapy (ART) varies widely across regions, from 25.5% in Dilla (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) to as high as 60% in Benishangul Gumuz (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), reflecting differences in socio-economic conditions and access to health services.\u003c/p\u003e \u003cp\u003eNutritional status reflects the balance between dietary intake and the body\u0026rsquo;s physiological needs, supporting growth, recovery, and immune function (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Disruption of this balance leads to malnutrition, manifested as undernutrition, micronutrient deficiency, or overweight (\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Among people living with HIV (PLHIV), malnutrition and HIV create a vicious cycle: malnutrition weakens immune function, while HIV increases nutrient requirements, reduces food intake and absorption, and alters metabolism, leading to weight loss and further immune suppression (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUndernutrition among PLHIV remains a critical challenge in sub-Saharan Africa, with reported prevalence ranging from 10\u0026ndash;13% in South Africa (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), 19.4% in Tanzania (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), and 13.8% in Ghana (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In Ethiopia, undernutrition among HIV-positive adults remains high, reaching 27.4% in 2021 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Despite global commitments under the Sustainable Development Goals (SDGs) to end hunger and ensure universal access to nutritious food, persistent inequalities, food insecurity, and rising living costs continue to hinder progress (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Inadequate facility capacity and shortages of nutritional supplements further constrain effective nutritional care for PLHIV (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePoor nutrition accelerates HIV progression, impairs immunity, and reduces physical and mental well-being (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Limited dietary diversity characterized by consumption of foods from few food groups remains widespread, with about one-third of PLHIV lacking adequate dietary knowledge and practices (\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Although nutrition counseling and education are essential for improving dietary diversity and treatment outcomes, implementation remains inconsistent, particularly in southern Ethiopia.\u003c/p\u003e \u003cp\u003eStudies have done so far have linked malnutrition in this group to poor dietary diversity, household food insecurity, tobacco use, depression, and inadequate nutrition counseling (\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Although Ethiopia has developed national HIV and nutrition policies (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), implementation remains suboptimal, with many undernourished patients discharged without receiving standard nutritional therapy (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Evidence on the nutritional status of PLHIV in Ethiopia is also scarce, and reported prevalence of underweight varies widely across regions and countries, particularly in sub-Saharan Africa (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the Wolaita Zone, where HIV prevalence is estimated at 0.4% and antiretroviral therapy (ART) coverage reaches 84.7% (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), information on the nutritional status of PLHIV and its determinants remains insufficient. The few available data are largely derived from single-facility studies. For example, a study conducted in 2017 reported an undernutrition prevalence of 26.6% among PLHIV (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), highlighting the need for more comprehensive, multi-facility investigations to better capture the regional burden.\u003c/p\u003e \u003cp\u003eThere is growing recognition that nutrition is a core component of effective HIV care. The World Health Organization has emphasized integrating nutritional support into national HIV/AIDS strategies (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). However, in Ethiopia, nutrition has not yet been fully operationalized as a central element of HIV care programs (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to assess the nutritional status and identify factors associated with malnutrition among adults living with HIV in South Ethiopia. The findings are intended to inform policymakers and program implementers, strengthen integrated HIV\u0026ndash;nutrition interventions, improve dietary counseling, and ultimately enhance treatment outcomes and quality of life among PLHIV.\u003c/p\u003e"},{"header":"2. Materials and Method","content":"\u003cp\u003e \u003cb\u003eStudy design and period\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA multi-facility cross-sectional study was conducted from January 15 to March 30, 2025, to assess the nutritional status and associated factors.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy settings\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe study was conducted in the Wolaita Zone of southern Ethiopia, located approximately 342 km south of Addis Ababa. The zone has an estimated population of 2.8\u0026nbsp;million and is administratively divided into 23 districts (16 rural and 7 urban) and 355 kebeles (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Wolaita zone, the political and administrative center of the region, is a hotspot for HIV transmission and in-migration. Antiretroviral therapy (ART) services are provided in 20 health facilities, including 7 public hospitals, 2 non-governmental hospitals, and 11 health centers, serving about 4,649 adults on ART.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy participants\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAntiretroviral therapy (ART) registers maintained at the selected health facilities were used as the sampling frame. The study population consisted of adults living with HIV who had been receiving ART for at least six months. Eligible participants were aged 18 years or older, who were taking ART for at least six months prior to the study, and were actively enrolled in ART care. Pregnant or lactating women, patients with edema, individuals who were critically ill, and those unable to communicate were excluded from the study.\u003c/p\u003e \u003cp\u003eA multistage sampling technique was employed. First, three public hospitals, four health centers, and one non-governmental hospital were selected using a lottery method. Sample size was then proportionally allocated to each facility based on the number of adults on ART (Fig.\u0026nbsp;1). Participants were selected using systematic random sampling, with a sampling interval of four (K\u0026thinsp;=\u0026thinsp;n). The first participant at each facility was selected by lottery, and subsequent participants were enrolled at regular intervals.\u003c/p\u003e \u003cp\u003e \u003cb\u003eVariables\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDependent variable\u003c/strong\u003e \u003cp\u003eNutritional status, determined by Body Mass Index (BMI).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eIndependent variables\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSocio-demographic and economic factors\u003c/strong\u003e \u003cp\u003eage, sex, residence, education, occupation, income, wealth index, marital status, family size, and religion.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDietary factors\u003c/strong\u003e \u003cp\u003emeal frequency, dietary diversity, and nutrition knowledge, attitudes, and practices.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eMedical and immunological factors\u003c/strong\u003e \u003cp\u003eCD4 count, WHO clinical stage, ART duration and regimen, opportunistic infections, diarrhea, and anemia.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eBehavioral and personal factors\u003c/strong\u003e \u003cp\u003esubstance use depression, stigma \u0026amp; discrimination, and physical activity.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSchematic Presentation of Sample Drawing\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFigure 1: Schematic representation of sampling procedure in PLHIV, Wolaita zone, 2023.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNB\u003c/b\u003e: \u003cem\u003ePPS: - \"probability proportionate to size\" or PPS sampling and SRS:- systematic random sampling\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eSample Size and Sampling Procedure\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe sample size was initially calculated using a single population proportion formula:\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;Z\u0026sup2;p(1\u0026thinsp;\u0026minus;\u0026thinsp;p)/d\u0026sup2;, based on a 25.2% prevalence of undernutrition among adults receiving ART (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), a 5% margin of error, a 95% confidence level, and a design effect of 2. After adding a 10% allowance for non-response, the minimum required sample size was 638 participants.\u003c/p\u003e \u003cp\u003eTo ensure adequate power for identifying factors associated with malnutrition, a second sample size estimation was performed using Epi Info version 7 with a double-population proportion formula. Malnutrition (underweight or overweight) was considered the outcome variable. Based on evidence from southwest Ethiopia showing that being single was associated with 2.2 times higher odds of underweight, a 1:1 case-to-control ratio, 5% significance level (two-sided), and 80% power were applied. This yielded a required sample size of 842. After accounting for a 10% non-response rate, the final sample size was set at 927 participants (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Participants were selected using systematic random sampling with proportional allocation based on ART caseloads at each facility.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Collection tools and procedures\u003c/b\u003e \u003c/p\u003e \u003cp\u003eData were collected through face-to-face interviews using a structured questionnaire. The instrument captured information on socio-demographic characteristics, dietary habits, household food insecurity, behavioral and personal factors, physical activity, and HIV-related clinical variables. The questionnaire was initially prepared in English, translated into Wolaitato language, and back-translated to ensure consistency.\u003c/p\u003e \u003cp\u003eA pretest was conducted among 46 PLHIV (approximately 5% of the sample) at the ART clinic of Sodo Christian General Hospital. Based on the pretest, minor revisions were made to improve clarity and reduce interview time. These included adding items related to family relationships, revising meal frequency categories in the dietary diversity questionnaire, and reducing the total number of questions. Face validity was assessed during pretesting, and construct validity was ensured through clear operational definitions for all variables.\u003c/p\u003e \u003cp\u003e Anthropometric measurements were taken according to World Health Organization (WHO) guidelines. Excess clothing like jacket, scarf etc was requested to remove during body weight measurement. For height measurement, participants were requested to stand erect, looking straight in the horizontal plane with feet together and knees straight. Weight was measured to the nearest 0.1 kg using a calibrated Seca digital scale, and height to the nearest 0.1 cm using a portable stadiometer (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Household food insecurity was assessed using the Food Insecurity and Nutrition Assessment for PLHIV Tool (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Substance use was evaluated with the WHO Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST v3.1) (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e), categorizing participants as low, moderate, or high risk (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Dietary diversity was measured using the FAO Women\u0026rsquo;s Dietary Diversity Questionnaire, adapted to local food items (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe questionnaire was first prepared by English and then translated in to Wolaitato language. The tools were pretested in 46 PLHIV (about 5% of the study participants) at ART site of Sodo Christian general Hospital. After pretesting, relationship with family members was included, food eating frequency in dietary diversity questionnaire was changed from 5 times per day [i.e. breakfast, lunch, afternoon (snack), evening (snack) and dinner] to 4 times per day [i.e. breakfast, lunch, afternoon (snack), and dinner]. To shorten the interview time the number of questioners was reduced. Both face and construct validation of questioner was assured. face validation was assessed during pretesting and modifications were made to make the question more understandable. Construct validation was ensured by making an accurate operational definition for each variable.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy definitions\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOne of the continuous variables in this study was age, it was categorized into three equally spaced groups: 18\u0026ndash;34 years, 35\u0026ndash;51 years, and \u0026ge;\u0026thinsp;52 years. Other continuous variables, including body mass index (BMI), monthly income, family size, duration of antiretroviral therapy (ART), and dietary diversity score, were categorized using established external criteria such as World Health Organization guidelines and relevant national protocols and manuals. Nutritional status, the primary outcome variable, was assessed using BMI in accordance with the Asian BMI cut-off standards (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eBody Mass Index(BMI)\u003c/b\u003e was calculated as weight (kg) divided by height squared (m\u0026sup2;) and classified as underweight (\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;), normal (18.5\u0026ndash;24.9 kg/m\u0026sup2;), or overweight (\u0026ge;\u0026thinsp;25 kg/m\u0026sup2;) (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eMalnutrition\u003c/b\u003e: is defined as a deficiency, excess, or imbalance in the intake of energy and/or nutrients. It encompasses two major forms: undernutrition (underweight) and over nutrition, which includes overweight and obesity (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNutritional status\u003c/strong\u003e \u003cp\u003eBalance between nutrient intake and physiological requirements (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePhysical activity\u003c/strong\u003e \u003cp\u003eCategorized as high, moderate, or low according to WHO guidelines (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eWealth index\u003c/strong\u003e \u003cp\u003eConstructed via principal component analysis of household assets, with internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.86).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical and Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eData were collected using KoboToolbox, cleaned, and analyzed using STATA version 17. Descriptive statistics were used to summarize participants\u0026rsquo; socio-demographic characteristics, HIV-related clinical factors, dietary diversity, household food insecurity, and nutritional status. Results were presented using frequencies, percentages, means with standard deviations, and medians with ranges, as appropriate.\u003c/p\u003e \u003cp\u003eNormality of continuous variables was assessed using visual inspection of histograms and the Kolmogorov\u0026ndash;Smirnov test. Variables that deviated from normal distribution, including CD4 count and duration of antiretroviral therapy (ART), were log-transformed to approximate normality. Categorical independent variables with more than two categories were converted into dummy variables, with the number of dummy variables equal to one less than the number of response categories. Reference categories were defined a priori.\u003c/p\u003e \u003cp\u003eAssumptions of multinomial logistic regression including independence of observations, absence of multicollinearity, linearity of continuous variables with the logit, and independence of irrelevant alternatives were assessed before model fitting. Bivariate multinomial logistic regression was performed to identify candidate variables for multivariable analysis using a p-value threshold of \u0026le;\u0026thinsp;0.25. Variables meeting this criterion were included in the multivariable multinomial logistic regression model to identify independent predictors of nutritional status.\u003c/p\u003e \u003cp\u003eAdjusted relative risk ratios (ARRs) with 95% confidence intervals were reported. Model fit was assessed using the variance inflation factor (found that VIF\u0026thinsp;\u0026lt;\u0026thinsp;2), and statistical significance was declared at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Quality Assurance\u003c/b\u003e \u003c/p\u003e \u003cp\u003eData collectors and supervisors received three days of training covering study objectives, ethical considerations, interview techniques, and standardized anthropometric measurement procedures. Data collection was conducted by eight trained BSc-level data collectors under the supervision of two MSc-level nutrition professionals. All measurement instruments were calibrated daily using standard weights to ensure accuracy. Supervisors conducted daily reviews of completed questionnaires to check for completeness, consistency, and data quality. The Nutrition Care and Support Guidelines for people living with HIV (PLHIV) were strictly followed throughout the data collection process. Interviews were conducted in private settings to maintain participant confidentiality.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEthical Considerations\u003c/b\u003e \u003c/p\u003e \u003cp\u003e Ethical approval\u003c/strong\u003e was obtained from the Institutional Review Board of Wolaita Sodo University (Ref. No. WSU-IRBC/016/2024). Official permissions were also secured from the Wolaita Zonal Health Department and all participating health facilities. The study was conducted in accordance with the principles of the Declaration of Helsinki. All participants were provided with clear information about the study\u0026rsquo;s objectives, procedures, potential benefits, and minimal risks prior to participation. Participation was entirely voluntary, and participants were informed of their right to withdraw from the study at any time without any consequences. Written informed consent was obtained from all participants before enrollment. Confidentiality and anonymity were strictly maintained, no incentives were offered, and participants identified with severe malnutrition or other medical conditions were referred to appropriate nutritional or clinical services.\u003c/p\u003e \u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e \u003cb\u003eSocio-Demographic Characteristics and Nutritional Status\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOf the 927 adults living with HIV approached, 921 participated in the study, giving a response rate of 99.4%. Slightly more than half were female (53.5%), and about two-thirds (67.97%) lived in urban areas. The mean age was 42.98 years (SD\u0026thinsp;\u0026plusmn;\u0026thinsp;11.55), with most participants (57.98%) aged 35\u0026ndash;51 years. The average monthly household income was 4,163.95 Ethiopian Birr (SD\u0026thinsp;\u0026plusmn;\u0026thinsp;3,589.66), and the mean household size was 4.46 persons (SD\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62). The mean body weight and height were 59.36 kg (SD\u0026thinsp;\u0026plusmn;\u0026thinsp;12.38) and 164.58 cm (SD\u0026thinsp;\u0026plusmn;\u0026thinsp;8.17), respectively, yielding a mean BMI of 23.89 kg/m\u0026sup2; (SD\u0026thinsp;\u0026plusmn;\u0026thinsp;4.15).\u003c/p\u003e \u003cp\u003eHalf of the participants were married (50.81%), among whom 25.43% were underweight and 23.50% overweight. Nearly half (49.09%) identified as protestant with underweight and overweight prevalence of 20.13% and 24.12%, respectively. Farmers or homemakers comprised 29.86% of the sample, of whom 21.45% were underweight and 25.09% overweight. More than two-thirds (64.17%) were heads of households, with 18.95% underweight and 24.09% overweight (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe wealth index, constructed using principal component analysis, demonstrated high internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.856). Based on EDHS classifications, the largest proportion of participants (25.8%) fell within the middle wealth quintile, where 18.91% were underweight and 17.65% were overweight.\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-demographic characteristics among adult people living with human immunodeficiency virus, South Ethiopia, 2025\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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eUnderweight #\u003c/b\u003e(\u003cb\u003e%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eOverweight #\u003c/b\u003e(\u003cb\u003e%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eNormal #\u003c/b\u003e(\u003cb\u003e%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAge in a complete years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;34 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48( 25.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43(22.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100(52.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u0026ndash;51 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101(18.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132(24.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e301(56.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31(15.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48(24.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117(59.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender of the respondents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74(19.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88(23.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e220(53.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106(19.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e135(25.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e298(55.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePlace of residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61(20.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79(26.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e155(52.54)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119(19.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144(23.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e363(57.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119(25.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e110(23.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e239 (51.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(15.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32(29.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60(55.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(12.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55(28.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117 (59.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeparated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(18.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(25.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33(55.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(10.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(12.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69(9.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRelationship to the household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112(18.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e143(24.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e336(56.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61(25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60(24.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e123 (50.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSon/daughter, homeless/street communities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(8.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(23.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59(68.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eOccupation of the participant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmer and house wife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59(21.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69(25.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e147(53.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGovernment employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(12.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(22.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70(64.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-Government employee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(17.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(13.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61(69.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDaily laborer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(26.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39(23.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82(50.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMerchant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37(19.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49(25.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e104(54.74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarpenter, retired, students, Solder, driver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(12.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30(31.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54(56.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eReligion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrthodox\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72(18.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102(25.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e225(56.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91(20.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e109(24.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e252(55.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCatholic, Muslim, pagans\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(24.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(17.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41(58.57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eEducational status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo formal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53(29.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39(21.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89(49.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52(17.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73(24.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e168(57.34)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53(24.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58(27.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e103(48.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVocational and diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(8.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22(17.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90(73.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDegree and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(10.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31(28.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68 (61.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eWealth index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42(32.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30(23.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56(43.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(18.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43(24.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e101(57.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45(18.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(17.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e151(63.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41(19.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65(30.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e105(49.43)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(11.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43(25.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e105(62.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c\u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eNutritional Status of Participants\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003cp\u003eBoth undernutrition and overweight were prevalent, demonstrating a double burden of malnutrition among PLHIV. The overall prevalence of malnutrition was 43.75%, including 19.54% (95% CI: 16.98\u0026ndash;22.11%) undernourished, 24.00% (95% CI: 21.44\u0026ndash;26.98%) overweight, and 56.46% (with normal BMI (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\u003eNutritional status of study participants (n\u0026thinsp;=\u0026thinsp;921)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight(BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.98\u0026ndash;22.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal weight (BMI 18.5\u0026ndash;24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.03\u0026ndash;59.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight (BMI\u0026thinsp;\u0026ge;\u0026thinsp;25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.44\u0026ndash;26.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eAntiretroviral therapy-related and clinical characteristics\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003cp\u003eAlmost half (44.8%) had received ART for \u0026ge;\u0026thinsp;15 years, and 67.21% had disclosed their HIV status to family or caregivers. Only 5.97% had ever diagnosed as having malnutrition; nearly all received therapeutic food, with 78.18% of cases recorded in 2023. A small fraction (2.6%) experienced recurrent malnutrition. Nearly all respondents (99.9%) reported not sharing therapeutic food with family members.\u003c/p\u003e \u003cp\u003eApproximately 5.3% experienced ART interruption, while 0.3% discontinued due to undernutrition concerns. Only 3% reported acute illness, and 5.3% had doctor-diagnosed food allergies.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNutritional Knowledge and Nutrition-Related Characteristics\u003c/b\u003e \u003c/p\u003e \u003cp\u003eNutritional knowledge was assessed using six items (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.80). Using PCA, responses were recoded into \u0026ldquo;adequate\u0026rdquo; (\u0026gt;\u0026thinsp;50%) and \u0026ldquo;inadequate\u0026rdquo; (\u0026le;\u0026thinsp;50%) knowledge categories.\u003c/p\u003e \u003cp\u003eOverall, 81.0% demonstrated adequate knowledge, while 19.0% had inadequate knowledge. Among those with inadequate knowledge, 32.22% were underweight and 8.07% overweight, whereas among those with adequate knowledge, 67.78% were underweight and 27.48% overweight.\u003c/p\u003e \u003cp\u003eUndernutrition was more frequent among participants with \u0026ge;\u0026thinsp;180 months of ART, HIV status disclosure (61.11%), absence of nutritional screening (51.11%), and inadequate dietary diversity (63.89%). Conversely, overweight was also more common among long-term ART users, those who had disclosed their HIV status (70.85%), and those never diagnosed with malnutrition (92.83%) (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\u003eCross tabulation of Nutrition Knowledge and Nutritional Characteristics among study participants (n\u0026thinsp;=\u0026thinsp;921)\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\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\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnderweight#(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverweight#(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNormal #(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eInadequate basic nutritional Knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInadequate (\u0026le;\u0026thinsp;50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58(32.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18(8.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99(19.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdequate (\u0026gt;\u0026thinsp;50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e122(67.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e205(27.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e419(80.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDuration on ART in months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30(16.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45(20.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66(12.74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61\u0026ndash;120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17(9.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25(11.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48(9.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121\u0026ndash;180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60(33.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64(28.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e153(29.54)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73(40.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e89(39.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e251(48.46)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDisclosure of HIV status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110(61.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e158(70.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e351(67.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70(38.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65(29.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e167(32.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eScreening for nutritional status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88(48.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60(26.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e144(27.80)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92(51.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e163(73.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e374(72.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEver diagnosed as having malnutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24(13.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16 (7.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15(2.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e156(86.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e107(92.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e503(97.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDietary diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInadequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e115(63.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e126(56.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e275(53.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65(36.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e97(43.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e243(46.91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSource of food groups obtained from\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOne source\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71(39.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e135(60.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e219(42.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026thinsp;+\u0026thinsp;sources\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109(60.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e88(39.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e299(57.72)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDietary allergy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10(5.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14(6.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25(4.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e170(94.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e209(93.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e493(95.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHistory reduced appetite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29(16.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10(4.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54(10.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e151(83.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e213(95.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e464(89.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSwallowing problem over the past 3\u0026ndash;6 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6(3.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3( 1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24(4.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e174(96.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e220(98.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e494(95.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA history of psychosocial or physical disabilities likely to cause weight loss\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45(25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21(9.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72(13.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e135(75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e202(90.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e446(86.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA history of clothes and/or jewelry that have become loose-fitting (weight loss)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76(42.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34(15.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e114(22.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e104(57.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e189(84.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e404(77.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003eDietary Habits\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003cp\u003eMost participants (95%) recognized the importance of dietary diversity; however, barriers included lack of food availability (22%) and financial constraints (52%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eBehavioral and personal factors\u003c/b\u003e \u003c/p\u003e \u003cp\u003ePhysical activity levels were generally low. Only 13.1% engaged in vigorous activity, and 90.1% were inactive or exercised fewer than three days per week. Based on standardized criteria, 5.5% were minimally active and 4.3% were classified as active. Moderate physical activity was reported by 22.3%, while 38.2% reported walking or cycling for at least 10 minutes, with 21.1% doing so three to five days per week (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlcohol use was reported by 18.0% of participants, with 38.6% drinking daily. Among alcohol users, 16.3% were underweight and 23.5% overweight. Khat chewing and tobacco smoking were reported by 14.4% and 9.8%, respectively. Among smokers, 24.4% were underweight and 28.9% were overweight. Stigma or discrimination related to HIV was experienced by 25.6% of participants, among whom 26.3% were underweight and 23.7% overweight. More than half (54.7%) reported lacking social support for adequate nutrition. Depressive symptoms were reported by 20.1%, including 38.2% with mild and 6.2% with moderate-to-severe symptoms (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\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\u003eCross tabulation of dietary habit and behavioral factors among study participants (n\u0026thinsp;=\u0026thinsp;921)\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 \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnderweight#(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverweight#(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNormal #(%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDid you eaten fruits this week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94(52.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137(61.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e333(64.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86(47.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86(38.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e185(35.71)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of servings fruits in a days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100(55.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93(41.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e209(40.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80(44.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e130(58.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e309(59.65)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eConsume vegetables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87(48.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e142(63.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e344(66.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93(51.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81(36.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e174(33.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of days consumed vegetables per week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;2 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77(42.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111(49.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e300(57.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103(57.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112(50.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e218(42.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of servings vegetables in a days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;2 servings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77(42.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111(49.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e300(57.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026thinsp;+\u0026thinsp;servings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103(57.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112(50.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e218(42.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eType of oil or fat is most often used for meal preparation in your HH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVegetable oil \u0026amp;/or butter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(17.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38(17.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e126(24.32)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLard or suet \u0026amp;/or margarine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55(30.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104(46.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e213(41.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot use oil or fat in their meal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93(51.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81(36.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e179(34.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEngaged in Vigorous intensive activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(19.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(34.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55(45.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e156(19.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e181(22.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e463(57.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDays in a week Vagarious intense activity (VIA) performed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1500 MET(\u0026lt;\u0026thinsp;5 D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(16.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(33.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15(50.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1500 MET(\u0026ge;\u0026thinsp;5 D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(17.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(12.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64(70.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo VIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e159(19.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e202(25.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e439(54.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDays in a week VIA performed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1500 MET(\u0026lt;\u0026thinsp;5 D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(16.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(33.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15(50.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1500 MET(\u0026ge;\u0026thinsp;5 D)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(17.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(12.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64(70.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo VIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e159(19.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e202(25.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e439(54.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTime spend in VIA on a typical day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026thinsp;+\u0026thinsp;minutes MIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21(17.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(17.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79(65.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo MIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e159(19.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e202(25.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e439(54.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModerate intense activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40(19.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53(25.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e112(54.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140(19.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e170(23.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e406(56.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLow intense activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67(19.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88(25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e197(55.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113(19.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e135(23.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e321(56.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVigorous intensity sports\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(10.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(25.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43(64.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e173(20.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e206(24.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e475(55.62)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModerate intensity sports\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(33.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(44.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(22.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e177(19.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e219(24.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e516(56.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEver drink alcohol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27(16.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39(23.49 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100(60.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e153(20.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e184(24.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e418(55.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChewing khat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(10.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30(22.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89(66.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e166(21.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e193(24.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e429(54.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSmoking tobacco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(24.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(28.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42(46.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158(19.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e197(23.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e476(57.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStigma and discrimination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62(26.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56(23.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e118(50.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118 (17.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167(24.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e400(58.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38(13.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63(23.16 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e171(62.87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45(18.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53(22.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e142(59.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65(18.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97(27.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e190(53.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate and severe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(56.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(17.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15(26.32)\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\u003eMedical and immunological factors\u003c/b\u003e \u003c/p\u003e \u003cp\u003eMost participants (83.6%) had CD4 counts\u0026thinsp;\u0026gt;\u0026thinsp;350 cells/mm\u0026sup3;, while 16.4% had\u0026thinsp;\u0026le;\u0026thinsp;350 cells/mm\u0026sup3;. Undernutrition was more prevalent among individuals with lower CD4 counts, whereas overweight predominated among those with higher counts. The majorities (91.1%) were classified as WHO clinical stage I, yet over one-third of participants in stage II or higher were undernourished. First-line ART was used by 93.1%, with comparable undernutrition across regimens. Comorbidities affected 18.1%, mainly hypertension, diabetes, and tuberculosis. Gastrointestinal symptoms were reported by 13.3%. Household food insecurity was common, with 58.9% reducing meal size and 17.3% unable to afford balanced diets.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFactors Associated with Nutritional Status\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn bivariate analysis, variables with p\u0026thinsp;\u0026le;\u0026thinsp;0.25 were entered into the multivariable multinomial regression model. Independent predictors of undernutrition included being a household head, secondary education (ARR\u0026thinsp;=\u0026thinsp;2.95), prior nutritional screening (ARR\u0026thinsp;=\u0026thinsp;2.11), lack of fruit consumption (ARR\u0026thinsp;=\u0026thinsp;1.96), physical inactivity (ARR\u0026thinsp;=\u0026thinsp;2.11), tobacco smoking (ARR\u0026thinsp;=\u0026thinsp;3.32), depression (ARR\u0026thinsp;=\u0026thinsp;8.26), skin infections (ARR\u0026thinsp;=\u0026thinsp;1.79), and CD4 count\u0026thinsp;\u0026lt;\u0026thinsp;350 cells/mm\u0026sup3;. Being a son/daughter or homeless (ARR\u0026thinsp;=\u0026thinsp;0.24) and khat chewing (ARR\u0026thinsp;=\u0026thinsp;0.19) were protective.\u003c/p\u003e \u003cp\u003ePredictors of overweight included larger family size (ARR\u0026thinsp;=\u0026thinsp;1.24), low dietary diversity (ARR\u0026thinsp;=\u0026thinsp;2.64), and no fruit intake (ARR\u0026thinsp;=\u0026thinsp;1.48). Protective factors were vocational or diploma-level education (ARR\u0026thinsp;=\u0026thinsp;0.49), middle wealth status (ARR\u0026thinsp;=\u0026thinsp;0.44), reduced appetite (ARR\u0026thinsp;=\u0026thinsp;0.29), engaging in \u0026ge;\u0026thinsp;30 minutes of daily physical activity (ARR\u0026thinsp;=\u0026thinsp;0.54), and khat chewing (ARR\u0026thinsp;=\u0026thinsp;0.25). Tobacco smoking (ARR\u0026thinsp;=\u0026thinsp;2.48) and skin infection (ARR\u0026thinsp;=\u0026thinsp;2.07) increased the risk of overweight (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultinomial regression analysis of Factors Associated with Nutritional Status of study participants (Reference\u0026thinsp;=\u0026thinsp;Normal Weight).\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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePredictor Variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eUnderweight Vs. Normal weighted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eOverweight Vs. Normal weighted\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCRR(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eARR(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCRR( 95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eARR( 95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSocio-demographic characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRelationship with HH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHead of household(HH)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.48(1.023\u0026ndash;2.16)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.27(0.80\u0026ndash;2.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.14( 0.79\u0026ndash;1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95(0.62\u0026ndash;1.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSon/daughter, homeless/street\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.35(0.15\u0026ndash;0.80)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.24(0.09\u0026ndash;0.59)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79 (0.46\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.64(0.35\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eEducational status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo formal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3.68(1.78\u0026ndash;7.57)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.28(1.20\u0026ndash;6.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96(.54- 1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.31(0.67\u0026ndash;2.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.91(0.94\u0026ndash;3.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.36(0.61\u0026ndash;3.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95(0.57\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.35(0.76\u0026ndash;2.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3.18(1.55\u0026ndash;6.52)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.95(1.33\u0026ndash;6.56)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.23(0.72\u0026ndash;2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.13(0.63\u0026ndash;2.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVocational and diploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75(0.30\u0026ndash;1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61(0.23\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53(0.28-1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.49(0.24\u0026ndash;0.99)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDegree and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95(0.85\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99(0.87\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.15(1.04\u0026ndash;1.28)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.24(1.10\u0026ndash;1.40)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eWealth index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3.93(2.11\u0026ndash;7.34)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.71(0.77\u0026ndash;3.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.30(0.74\u0026ndash;2.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.69(0.34\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.66(0.89\u0026ndash;3.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24(0.59\u0026ndash;2.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.03(0.62\u0026ndash;1.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57(0.30\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.56( 0.873-2.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06(0.53\u0026ndash;2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.67(0.41\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.44(0.25\u0026ndash;0.80)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.05(1.12\u0026ndash;3.73)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.45(0.73\u0026ndash;2.87)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.51(0.94\u0026ndash;2.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.19(0.70\u0026ndash;2.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNutritional and ART related factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNutritional screening\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.48(1.75\u0026ndash;3.52)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.11(1.35\u0026ndash;3.31)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95(0.67\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.85(0.56\u0026ndash;1.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDietary diversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInadequate or (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) food groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.56(1.10\u0026ndash;2.21)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.32(0.88\u0026ndash;1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.14(0.83\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.09(0.75\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdequate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFood source\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOne source\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88(0.62\u0026ndash;1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68(0.43\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.09(1.52\u0026ndash;2.88)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.64(1.76\u0026ndash;3.96)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026thinsp;+\u0026thinsp;sources\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHistory of reduced appetite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.65(1.01\u0026ndash;2.68)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71(0.36\u0026ndash;1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.40(0.20\u0026ndash;0.80)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.29(0.13\u0026ndash;0.66)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDietary habit\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEaten fruits in a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.64( 1.16\u0026ndash;2.32)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.96(1.26\u0026ndash;3.04)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.12(0.81\u0026ndash;1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.48(1.00-2.19)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity\u003c/b\u003e\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTime spend in MIA on a typical day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026thinsp;+\u0026thinsp;minutes MIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo MIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.89(1.17\u0026ndash;3.05)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.12(1.22\u0026ndash;3.69)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.74(.51-1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.54(0.35\u0026ndash;0.83)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePersonal and behavioral factors\u003c/b\u003e\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChewing khat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.40(0.22\u0026ndash;0.73)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.19(0.07\u0026ndash;0.49)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.74(0.47\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.25(0.11\u0026ndash;0.53)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSmoking tobacco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.57( .91-2.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3.32(1.25\u0026ndash;8.79)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.49(0.89\u0026ndash;2.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.48(1.09\u0026ndash;5.65)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStigma and discrimination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.56( 0.2\u0026ndash;0.94)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.33(0.82\u0026ndash;2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87(-0.23-0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.22(0.78\u0026ndash;1.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.35(-.13-0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.60(0.91\u0026ndash;2.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01(-.41-0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.87(0.53\u0026ndash;1.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.43(\u0026minus;\u0026thinsp;.018-0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.68(0.96\u0026ndash;2.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32(-.05-0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.23(0.77\u0026ndash;1.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate \u0026amp; severe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.26(1.55\u0026ndash;2.96)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e8.26(3.16\u0026ndash;21.60)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59( -0.25-1.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.74(0.95\u0026ndash;7.91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical and immunological properties\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSkin change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.11(.70-1.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.79(1.00-3.21)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.76(1.19\u0026ndash;2.62)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2.07(1.25\u0026ndash;3.44)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRef.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCD4 count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.14(0.94\u0026ndash;4.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e4.18(1.56\u0026ndash;11.16)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.83(0.84\u0026ndash;3.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.33(0.93\u0026ndash;5.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e201\u0026ndash;350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.71(1.07\u0026ndash;2.72)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.94(1.10\u0026ndash;3.39)*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.73(0.40\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76(0.42\u0026ndash;1.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eBN: MIA-Moderate Intense Activity, ARR-Adjusted relative risk, CRR-Crude relative risk, Vs-versus, CI-Confidence Interval, *-P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study demonstrates a substantial double burden of malnutrition among adults living with HIV (PLHIV) in South Ethiopia, with both underweight and overweight remaining highly prevalent. Nearly two in five participants (43.75%) were malnourished, comprising 19.54% underweight and 24.21% overweight, highlighting the coexistence of nutritional deficiency and excess within the same population. This overall burden is comparable to findings from Ghana (42%) (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) but exceeds reports from South Africa (39%) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), underscoring persistent nutritional vulnerability among PLHIV in low-resource settings.\u003c/p\u003e \u003cp\u003eThe prevalence of underweight observed in this study was lower than reports from several Ethiopian settings (26.3\u0026ndash;37.2%) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e) but higher than estimates from Kenya (8%) (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). It closely aligns with findings from Nepal (18.3%) (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e) and Tanzania (19.4%) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), and falls within the pooled estimate for sub-Saharan Africa (23.7%) (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Variations across studies may reflect differences in ART coverage, socioeconomic conditions, food security, and access to nutrition services. Conversely, overweight was more prevalent than underweight, mirroring patterns reported in South Africa (26%) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), but exceeding national Ethiopian estimates (9.6\u0026ndash;21%) (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Although lower than levels reported in Zimbabwe, Cameroon, and Uganda (\u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e), the observed prevalence suggests a nutrition transition among PLHIV, potentially driven by urbanization, dietary shifts toward energy-dense foods, and sociocultural norms favoring higher body weight.\u003c/p\u003e \u003cp\u003eSocio-demographic factors played a significant role in shaping nutritional outcomes. Participants who were sons or daughters within households or homeless community members had markedly lower odds of underweight, consistent with findings from Addis Ababa (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). This may reflect shared household resources and informal social support mechanisms that buffer food insecurity. In contrast, secondary education was associated with increased odds of underweight, aligning with evidence from Ethiopia and Bangladesh (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). This counterintuitive association may reflect disparities in employment opportunities, income stability, or rural\u0026ndash;urban differences in food access and lifestyle, emphasizing that education alone does not guarantee nutritional adequacy. This may reflect the social and economic support available within shared or extended households. Participants with secondary education were nearly three times more likely to be underweight (ARR\u0026thinsp;=\u0026thinsp;2.78, 95% CI: 1.25\u0026ndash;6.16), supporting evidence from Ethiopia (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e) and Bangladesh (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e) that education influences health literacy, income, and diet. Differences from other Ethiopian studies (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e) could result from urban\u0026ndash;rural variation and ART program support.\u003c/p\u003e \u003cp\u003eThe association between nutritional screening and underweight likely reflects reverse causation, whereby individuals are screened after clinical suspicion of malnutrition rather than screening preventing its occurrence (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). Similarly, limited dietary diversity and lack of fruit intake were strongly associated with underweight, reinforcing evidence that monotonous diets dominated by staple foods may provide sufficient energy but fail to meet micronutrient needs critical for immune function among PLHIV (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBehavioral and psychosocial factors emerged as important determinants. Physical inactivity significantly increased the risk of underweight, consistent with studies from Ethiopia, Korea, and China (\u003cspan additionalcitationids=\"CR68\" citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e). Regular physical activity supports lean body mass, appetite regulation, and immune competence, while inactivity may accelerate wasting in chronic illness (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). Tobacco smoking showed a strong association with underweight, corroborating findings from Ethiopia, Nepal, and South Africa (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e), likely due to appetite suppression and increased metabolic demand. Depression was one of the strongest predictors of underweight, with affected individuals exhibiting markedly higher risk, consistent with evidence from Ethiopia, the Philippines, and Nigeria (\u003cspan additionalcitationids=\"CR74\" citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e). This underscores the critical interplay between mental health and nutritional status in HIV care.\u003c/p\u003e \u003cp\u003eClinical factors further influenced nutritional outcomes. Skin infections and low CD4 counts were strongly associated with underweight, reflecting the bidirectional relationship between infection, immune suppression, and nutritional depletion (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e). These findings reinforce the importance of early infection management and immunological monitoring to prevent nutritional decline.\u003c/p\u003e \u003cp\u003eRegarding overweight, vocational or diploma-level education and middle wealth status were protective, consistent with studies from Ethiopia, Nigeria, and Zimbabwe (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e). In contrast, poor dietary diversity and lack of fruit intake increased overweight risk, suggesting reliance on energy-dense but nutrient-poor diets (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Regular physical activity reduced the likelihood of overweight, in agreement with prior evidence (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e). Although khat chewing was inversely associated with overweight, its known adverse health effects warrant caution in interpretation (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e). The association between skin infections and overweight observed in this study aligns with findings from Namibia and Uganda (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e), and may reflect inflammatory or treatment-related metabolic changes.\u003c/p\u003e \u003cp\u003eThis study highlights the strong influence of socio-economic, behavioral, and clinical factors on the nutritional status of adults living with HIV. Underweight was more common among individuals with lower education, dependent household roles, lower wealth status, depression, skin infections, and low CD4 counts, reflecting compounded social and immunological vulnerability. Both underweight and overweight were more prevalent among economically disadvantaged participants, underscoring the dual burden of malnutrition. Reliance on single food sources and physical inactivity increased the likelihood of unhealthy weight outcomes, while dietary diversity and regular physical activity were protective. Tobacco smoking elevated the risk of malnutrition, whereas khat chewing was associated with lower odds. These findings emphasize the need for integrated, nutrition-sensitive HIV care addressing social, behavioral, and clinical determinants.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study revealed a substantial burden of malnutrition among adults living with HIV in South Ethiopia, with both underweight and overweight emerging as significant public health concerns. The simultaneous presence of these conditions reflects an ongoing nutritional transition within this population. Underweight was strongly associated with inadequate dietary practices, physical inactivity, tobacco use, depression, skin infections, and low CD4 counts. Nutritional screening and secondary education were also linked to increased underweight risk, while being a son or daughter within a homeless household and khat chewing showed reduced likelihood associations.\u003c/p\u003e \u003cp\u003eOverweight was less common among participants with vocational or diploma education, those in the middle wealth category, individuals reporting reduced appetite, those engaging in daily physical activity, and khat chewers. In contrast, low dietary diversity, lack of fruit intake, tobacco smoking, skin infections, and larger family size significantly increased the likelihood of overweight.\u003c/p\u003e \u003cp\u003eAddressing this dual burden of malnutrition requires coordinated action. Policy efforts should prioritize nutrition-sensitive HIV programs, ensure consistent access to food and micronutrient supplements, and strengthen community-based support systems. Enhancing Multi-Sectoral collaboration between health, agriculture, and social protection sectors is essential to improve nutritional outcomes, support treatment adherence, and ultimately enhance the quality of life of people living with HIV.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eART, Antiretroviral Therapy; COA, Currently On ART; HC, Health Center; PH, Primary Hospital; PLHIV, People living with HIV/AIDS; LMIC, Low and Middle-Income Countries; WSUCSH, Wolaita Sodo University Comprehensive Specialized Hospital.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eAll data supporting the findings of this study are available within the paper and its Supplementary Information.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eI would like to express my gratitude to Wolaita Sodo University College of Medicine and Health Science for allowing me to develop this thesis. I am grateful to the Health Office of the Wolaita Sodo Health Administration Zone for providing us with the necessary information essential for the accomplishment of the research work. Finally, I express my appreciation to the study participants, data collectors, and everyone who assisted in completing the research. Their contributions in translation to the local language and encouragement are highly appreciated.\u003c/p\u003e\n\u003ch2\u003eConsent to participate declaration\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThis study was conducted in full accordance with the ethical principles outlined in the Declaration of Helsinki. Ethical clearance was taken from Institutional Review Board (IRB) of Wolaita Sodo University: Ref. No. WSU-IRBC/016/2024. All procedures involving human participants were reviewed and approved by IRB. \u0026nbsp;Prior to enrollment, participants were provided with full information about the study\u0026rsquo;s purpose, procedures, potential benefits, and minimal risks. They were also informed of their unconditional right to decline participation or withdraw at any stage without penalty or effect on the services they receive. Confidentiality and privacy were maintained thoroughly.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eConsent for Publication\u003c/h2\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interest.\u003c/p\u003e\n\u003ch2\u003eAuthor Contributions\u003c/h2\u003e\n\u003cp\u003eA.A: Conceptualization, writing \u0026ndash; original draft preparation, data curation, formal analysis, investigation, methodology, project administration, resources, software.\u0026nbsp;EW: Methodology, project administration, resources, software, supervision, validation, visualization, writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;AA: Methodology, project administration, resources, software, supervision, validation, visualization, writing review \u0026amp; editing. All authors have read and approved the final version submitted.\u003c/p\u003e\n\u003ch2\u003eFunding Information\u003c/h2\u003e\n\u003cp\u003eThis is a self-funded research project with technical support from Wolaita Sodo University Collage of Health Science and Medicine.\u003c/p\u003e\n\u003ch2\u003eSupplementary files\u003c/h2\u003e\n\u003cp\u003eEnglish version questioner\u003c/p\u003e\n\u003cp\u003eEthical Clearance Certificate\u003c/p\u003e\n\u003cp\u003eData set used for Analysis\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGovender RD, Hashim MJ, Khan MA, Mustafa H, Khan G. Global epidemiology of HIV/AIDS: a resurgence in North America and Europe: Available. 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DovePress: Patient Preference Adherence. 2022;16:1703\u0026ndash;17112. Patient Prefer Adherence. https://doi.org/10.2147/PPA.S360517.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEnichen E, Adams RB, Demmig-Adams B. Physical Activity as an Adjunct Treatment for People Living with HIV? Am J Lifestyle Med. 2023;17(4):502\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFathima S, Madhu A, Udaya Kumar M, Dhingra V, Kumar S, Singh N. Nutritional Aspects of People Living with HIV (PLHIV) Amidst COVID-19 Pandemic: an Insight. Curr Pharmacol Rep. 2022;8(5):350\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeldehaweria NB, Abreha EH, Weldu MG, Misgina KH. Psychosocial correlates of nutritional status among people living with HIV on antiretroviral therapy: A matched case-control study in Central zone of Tigray, Northern Ethiopia. PLoS ONE. 2017;12(3):e0174082.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdedeji WA, Ma Q, Raji AM, Cha R, Rasaki OM, Hutson A, et al. Prevalence of depression among people living with HIV in rural hospitals in South-Western Nigeria-Association with clinico-demographic factors. AIDS Res Therapy. 2023;20(1):89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElsayed H, O'Connor C, Leyritana K, Salvana E, Cox SE. Depression, Nutrition, and Adherence to Antiretroviral Therapy in Men Who Have Sex With Men in Manila, Philippines. Front public health. 2021;9:644438.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalil FS, Kabeta T, Jarso H, Hasen M, Ahmed J, Kabeta S. Determinants of undernutrition among adult people on antiretroviral therapy in Goba Hospital, Southeast Ethiopia: A case\u0026ndash;control study. DovePress. 2020;12:1\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://doi.org/10.2147/NDS.S276311\u003c/span\u003e\u003cspan address=\"10.2147/NDS.S276311\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShifera N, Yosef T, Matiyas R, Kassie A, Assefa A, Molla A. Undernutrition and Associated Risk Factors among Adult HIV/AIDS Patients Attending Antiretroviral Therapy at Public Hospitals of Bench Sheko Zone, Southwest Ethiopia. DOI: 10.1177/23259582221079154. J Int Association Providers AIDS Care (JIAPAC). 2022;21:1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalinjuma AV, Hussey H, Mollel GJ, Letang E, Battegay M, Glass TR, et al. Body mass index trends and its impact of under and overweight on outcome among PLHIV on antiretroviral treatment in rural Tanzania: A prospective cohort study. 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Clin Epidemiol Global Health. 2025;32:101953.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGilberti G, Tiecco G, Marconi S, Marullo M, Zanini B, Quiros-Roldan E. Weight gain, obesity, and the impact of lifestyle factors among people living with HIV: A systematic review. Obes reviews: official J Int Association Study Obes. 2025;26(7):e13908.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnikpe JN, Chukwu AJ, Edem EN, Elahmar AAE, Sinha S, Arome D. Effect of anthropometric and sociodemographic variables on physical activity levels of people living with human immunodeficiency virus/acquired immunodeficiency syndrome on highly active antiretroviral therapy. Tzu chi Med J. 2023;35(2):200\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOumer A. Khat consumption and undernutrition among adult population in Ethiopia: A systematic review and meta-analysis. PLoS ONE. 2024;19(4):e0299538.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDraganescu M, Baroiu L, Iancu A, Dumitru C, Radaschin D, Polea ED, et al. Perspectives on skin disorder diagnosis among people living with HIV in southeastern Romania. Experimental Therapeutic Med. 2021;21(1):97.\u003c/span\u003e\u003c/li\u003e\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-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nutn","sideBox":"Learn more about [BMC Nutrition](http://bmcnutr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nutn/default.aspx","title":"BMC Nutrition","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Fruit intake, nutritional status, physical activities, khat, tobacco smoking, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-8484488/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8484488/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eMalnutrition remains a major public health concern among adults living with HIV (PLHIV), yet evidence on its magnitude and its associated factors is limited in the study settings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eTo assess the nutritional status and associated factors among adults living with HIV.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA multi-facility cross-sectional study was conducted across four hospitals and four health centers selected using a lottery method. A total sample of 927 adults on antiretroviral therapy (ART) was proportionally allocated based on currently on antiretroviral therapy (COA) case load. Data were collected through face-to-face interviews using systematic random sampling. Nutritional status was classified using Body Mass Index (BMI): underweight (\u0026lt;18.5 kg/m²), normal (18.5–24.9 kg/m²), and overweight (≥25 kg/m²). Analyses were performed using STATA version 17. Multinomial logistic regression identified predictors of nutritional status at a 95% confidence level with p \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe prevalence of malnutrition was 43.75%, including 19.54% (95% CI: 16.98–22.11%) underweight and 24.21% (95% CI: 21.44–26.98%) overweight. Underweight was significantly associated with nutritional screening (ARR = 2.11, 95% CI: 1.35–3.31), secondary education (ARR = 2.95, 1.33–6.56), lack of fruit intake (ARR = 1.96, 1.26–3.04), physical inactivity (ARR = 2.12, 1.22–3.69), tobacco smoking (ARR = 3.32, 1.25–8.79), depression (ARR = 8.26, 3.16–21.60), skin infection (ARR = 1.79, 1.00–3.21), and low CD4 count (\u0026lt;200: ARR = 4.18, 1.56–11.16; 201–350: ARR = 1.94, 1.10–3.39). Reduced risk of underweight was observed among participants who were sons/daughters or homeless (ARR = 0.24, 0.09–0.59) and those who chewed khat (ARR = 0.19, 0.07–0.49).\u003c/p\u003e\n\u003cp\u003eOverweight was less likely among participants with vocational/diploma education (ARR = 0.49, 0.24–0.99), middle wealth status (ARR = 0.44, 0.25–0.80), reduced appetite (ARR = 0.29, 0.13–0.66), ≥30 minutes of daily physical activity (ARR = 0.54, 0.35–0.83), and khat chewers (ARR = 0.25, 0.11–0.53). Overweight was more likely among those relying on a single food group (ARR = 2.64, 1.76–3.96), lacking fruit intake (ARR = 1.48, 1.00–2.19), smoking tobacco (ARR = 2.48, 1.09–5.65), and having a skin infection (ARR = 2.07, 1.25–3.44). Additionally, each one-unit increase in family size increased the risk of overweight by 24% (ARR = 1.24, 1.10–1.40).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eMalnutrition among PLHIV presents a dual burden of underweight and overweight influenced by socio-demographic, dietary, behavioral, and clinical factors. Strengthening routine nutritional screening, delivering targeted dietary counseling, promoting physical activity, addressing mental health concerns, and improving management of infections are essential to enhance treatment outcomes and quality of life for PLHIV.\u003c/p\u003e","manuscriptTitle":"Nutritional status and its associated factors among adult People living with HIV: A Multi-facility level Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-21 04:35:22","doi":"10.21203/rs.3.rs-8484488/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-19T12:22:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-25T10:29:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"294808793674524295610623449709352175792","date":"2026-01-18T10:12:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-17T17:46:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224842331165403162094341807240914496712","date":"2026-01-16T15:13:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"270236554405406670281868816095246553765","date":"2026-01-16T15:03:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-16T14:48:03+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-05T11:51:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-05T09:39:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-05T09:37:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nutrition","date":"2025-12-30T22:25:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nutn","sideBox":"Learn more about [BMC Nutrition](http://bmcnutr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nutn/default.aspx","title":"BMC Nutrition","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ecc1c5ae-a39b-4366-8748-32a8160c5a46","owner":[],"postedDate":"January 21st, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T14:53:47+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-21 04:35:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8484488","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8484488","identity":"rs-8484488","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}