A Prevalence and Contributing Factors of Overweight and Obesity Among Office Public Servants in Case of Bahir Dar City Administration Public Sectors, Ethiopia

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Civil servants are exposed to the sedentary lifestyle, and some of these jobs are characterized by sitting for a long period of time. Therefore, civil servants become susceptible to developing overweight/obesity, but little was researched on behalf of office civil servants. Method: Institution based cross-sectional study using Simple random sampling method was used to select 365 office civil servants working in Bahir Dar city, Northwest Ethiopia in 2020. The data was collected by using semi-structured self-administered questionnaire. The data were entered in to Epi-data and analyzed on SPSS. Result: The prevalence of overweight or obesity was 30.83% among office public servants in case of Bahir Dar city. Obesity or overweight is associated with more than three times meal per day [AOR=4.34, 95% CI [2.22–8.33], regular physical exercise or intensive activity at work place or at home [AOR= 3.84, 95% CI 1.37–11.11], recline or by sitting within a day (sedentary behavior) [AOR= 10 95% CI 4.16– 50.00]. Conclusion and Recommendation: The prevalence of overweight or obesity was high among office civil servant workers in Bahir Dar city. Burden of overweight or obesity in this area is associated with time spent by sitting per day, meal consumption frequency, lunch consumption frequency and high intensity regular physical exercise which deserves sector wise integrated occupational health program in the work place to decrease identified risk factors of overweight or obesity. Social Work Overweight Obesity Civil Servant Summary of the article the manuscript aimed to assess the prevalence and associated factors of overweight and obesity among Bahir Dar city office public servants, Bahir Dar, Northwest Ethiopia in 2020. The results of this study can be used as a reference for program planners, policymakers, researchers, and organizations to design and implement an effective prevention and control strategies and programs that could address non-communicable diseases caused by overweight and obesity. The manuscript is drawn from a full length research paper done by the Authors included in the manuscript and sponsored by Bahirdar University. Manuscript begins with introduction, in the method section (study setting and participants, measurements, data analysis, ethical clearance, patient and public involvement) are included. In the result section (demographic information, prevalence of obesity/overweight and associated risk factors of overweight or obesity) are presented. Discussion, conclusion, recommendations, acknowledgment & funding, Authors’ Contributions are included. The manuscript of study tries to address a growing public health importance concern of the nation which is associated with many of the chronic diseases. Measurements of multiple variables having significance on overweight/obesity including level of physical activity were attempted to address. Although it is known that being overweight or obese brings a variety of health complications, no attempt was made to assess such issues in the study population. Recommendations for other researchers concerning issues not covered by this study are addressed for readers in the study. Introduction Overweight and obesity was defined as “abnormal or excessive accumulation of fat that may impair health” and formally recognized as a global epidemic in 1997 by WHO [ 1 ]. It is a disorder of energy metabolism that occurs when the balance between energy intake and expenditure is disrupted. It involves body fatness or excessive adipose tissue stores that can be associated with medical or psychosocial morbidity [ 2 ]. Body mass index (BMI) is used to classify overweight and obesity in adults commonly [ 1 ]. It is currently estimated that as much as 20–50% of urban populations in Africa are classified as either overweight or obese and that by 2025, three quarters of the obese population worldwide will be in non-industrialized countries. WHO had declared overweight as one of the top ten health risks in the world and one of the top five in developed nations [ 3 ]. In Africa, researchers and policy makers concentration was on malnutrition and infectious diseases. However, in recent times, a sharp rise in the incidence of obesity and chronic diseases has been observed and recognized as a major public health problem in many African countries [ 4 ]. Overweight/obesity seems an unusual concern in Ethiopia’s public health; however, the government revealed that being overweight/obesity is emerging fast as a non-communicable public health concern [ 5 , 6 ]. Despite the fact that physiological, genetic and environmental factors are contributing factors for weight gain, insufficient energy expenditure due to insufficient physical activity or sitting for prolonged periods is the main physiological factor [ 7 ]. This sedentary lifestyle with a dietary alteration (fast food) is a vital health behavior responsible for the remarkable increase in obesity or becoming overweight [ 8 , 9 ]. Although genetic factor plays significant role in overweight and obesity fast economic growth and development, urbanization, and changes in dietary and lifestyle patterns including the work, household, recreational, transportation, sedentary lifestyle, and physical inactivity also affects overweight and obesity. Overweight/obesity seems an unusual concern in Ethiopia’s public health; however, the government revealed that being overweight/obesity is emerging fast as a non-communicable public health concern [ 10 , 11 ]. Physical inactivity is identified as the fourth leading risk factor (6%) for global mortality next to high blood pressure, tobacco use and high blood glucose level. In many countries physical inactivity levels are increasing with major implications for the general health of the community and prevalence of non-communicable diseases worldwide [ 12 ]. Even though, the magnitude and severity of overweight and obesity is increasing from time to time, there are only few researches conducted on the prevalence and associated factors of overweight/obesity in office civil servants. As a result, there is lack of nationally representative data on the problem. Therefore, further studies are required to design and implement prevention, control and management strategies for overweight/obesity. Hence, the present study aims to provide baseline and reference data on the prevalence and associated factors of overweight and obesity among office civil servant workers in Bahir Dar city administration. Methods 2.1. Study Setting and Participants Institution based cross-sectional study design was conducted from June 01–15 /2020 among Office Public Servants in case of Bahir Dar city Administration public sectors. Bahir Dar city is located at an attitude of 1820 meters (5970ft) above sea level. The city is located approximately 578km north/north west of Addis Ababa. The city has 6 sub-cities namely; Fasilo, Tana, Atse Tewodros, Gish Abay, Belay Zeleke and Dagmawi Minilik. According to the city civil service department there were 36 civil servant offices/departments in Bahir Dar city directly accountable to the city administration and there were about 3651 (2016 male and 1645 female) civil servants who are working there [ 13 ]. To select study unit, ten out of thirty-six public service departments/offices namely: Mayor office, Transport, Finance and economic development, Health, House development, Social affairs, Women and children, First instance court, Civil Service and Tana sub-city departments were randomly selected. Study participants from ten offices/departments were selected by simple random sampling method after proportionally allocated to the ten offices to select required sample participants, Sample size was determined by single population proportion formula using Epi- Info version 7 software with the assumption of 95% confidence interval, 5% margin of error, and considering prevalence of overweight 47% (on a study done among office based urban civil servants in Southern nations, nationalities and peoples’ region, Ethiopia) [ 14 ], and adding 5% nonresponse rate which provides a total sample size of 365 individuals. 2.2. Measurements Most parts of the questionnaires were adapted from WHO steps instrument for chronic disease risk surveillance [ 15 ]. The data was collected by using semi-structured self-administered questionnaire. The questionnaire was prepared in English, translated to Amharic and then to English by language experts and finalized and administered in Amharic language which is widely spoken in the city. The data was collected on socio-demographic characteristics (sex, age, educational and marital status), and behavioral factors like alcohol consumption, dietary habits, physical activity and recreational activities. Anthropometric measurements of weight, and height were performed by using calibrated equipment and standardized techniques. Weight was recorded using a portable digital weight scale with a precision of 0.5 kilograms. BMI was calculated as BMI = Weight (kg)/ [Height (m)2]. According to the WHO classification of BMI, Less than 18.5 consider underweight, 18.5–24.9 normal weight, 25–29.9 overweight and ≥ 30 obese. Global Physical Activity Questionnaire developed by WHO for physical activity surveillance was used. The quality of data was ensured during collection, coding, entry and analysis. During the data collection time, adequate supervision and follow up was provided to the data collectors and were checked on 10% of the respondents. 2.3. Data Analysis Data were entered into EPI DATA version 3.2 Software and analyzed by Statistical Product and Service Solutions (SPSS) version 23. Descriptive statistics using frequencies, proportions and table were used to present the study results. Bivariate analysis was conducted to screen the possible determinants of overweight and obesity and variables with p-values of ≤ 0.2 regression analysis and important variables for the objective of the study based on literature review were entered to the multivariate model and stepwise forward regression procedure was employed. Associated factors were identified using binary logistic regression model. Finally, in multi-variable binary logistic regression analysis, factors associated with overweight/obesity were identified using their Adjusted Odds Ratio (AOR) with the corresponding 95% CI. Hosmer and Lemshow goodness of fit test were used to check whether the predictors adequately explain the response variable. The model fitness was checked by Hosmer- Lemeshow test. Hosmer and Lemshow goodness of fit test was declared at p-value of 0.05. Statistical significance was considered at significance level of 5%. 2.4. Ethical Clearance Prior to starting the work, the Ethical Review Committee of the Bahir Dar University approved the study proposal. The aim of the study was explained to study subjects and their values, culture, belief, religion and norms were respected. The survey forms did not include personal identifiers in order to protect confidentiality of patients. Both Written and Verbal informed consent were obtained from each participant. There was no invasive procedure performed to conduct this study, instead measuring of physical composition was performed. Privacy and confidentiality of each study participant were strictly kept and all overweight /obese civil servants were provided a brief information on overall risk factors of overweight and or obesity. All who participated in the study were acknowledged. 2.5. Patient and Public Involvement There was no invasive procedure performed to conduct this study, instead measuring of physical composition was performed. The study participants are not labeled as patients by physicians or they are not taken as peoples with known problems by themselves and also by the society rather they are civil servants found in a city of Bahirdar. Even though they are not considered as patients the status shown from the data needs to be considered keep confidential. The survey forms did not include personal identifiers in order to protect confidentiality of participants. Both Written and Verbal informed consent were obtained from each participant. The result will be planned to disseminate through seminars organized by the civil servant office of the city. Participants will be informed about result and if they agreed intervention will be made given by in collaboration with ministry of health. Result 3.1. Socio-Demographic Characteristics In this study, a total of 365 participants were recruited of them, 360 participated with overall response rate of 98.63%. From the respondents 164 (45.6%) were female. Regarding to respondent age majority of them was in the age group of (25–35 years) (43.3%). More than half of respondents were educated to the level of undergraduate degree (59.7%). About 70% of respondents were paid more than 4500 Ethiopian birr (252, 70%) (Table 1 ). Table 1 Socio-demographic characteristics of respondents among office civil servants in Bahir Dar city administration, Ethiopia, 2020 (n = 360). Variables Category Frequency Percent Sex (N = 360) Male 196 54.4 Female 164 45.6 Age (N = 360) 18-24yrs 19 5.3 25-35yrs 156 43.3 36-45yrs 144 40 > 45yrs 41 11.4 Educational level (N = 360) High school and below 9 2.5 Diploma 123 34.2 Undergraduate degree 215 59.7 Masters 13 3.6 Income (N = 360) 4500 252 70 Service year (N = 360) 6 month to 5 yrs. 72 20 5-10yrs. 160 44.4 11-15yrs. 116 32.2 > 15yrs. 12 3.3 Marital status (N = 360) Single 126 35 Married 214 59.4 Divorced 11 3.1 Widowed 9 2.5 3.2. Associated risk Factors of Overweight or Obesity In the bi-variable analysis age, income, Injera, bread and cereal foods, Meal frequency per day, Breakfast consumption pattern, Lunch consumption pattern, Dinner consumption pattern, Regular physical exercise (intensive activity at work place or at home), Moderate regular physical activity at work place or at home, Time you spend by recline or by sitting within a day (sedentary behavior), marital status, sugar and sweet foods, spent in sleeping within a day, doing high recreational activity and alcohol consumption were filtered. In the multivariable logistic regression analysis variables that showed statistically significant association with obesity and overweight using p-value < 0.05 were age, Meal frequency consumption pattern, lunch frequency consumption pattern, Time you spend by recline or by sitting within a day (sedentary behavior) and regular physical exercise or intensive activity at work place or at home. Respondents who were age 18–24 years [AOR = 9.09, 95% CI 1.16–83.33], 25–35 years [AOR = 6.66, 95% CI 4.00–33.33] and 36–45 [AOR = 5.49 95% CI [2.13–14.28] were less likely to be overweight/obesity as compared to those who were in, age above 45 years. Another risk factor was adults who took more than three times meal per day, more likely to overweight and obesity [AOR = 4.34, 95% CI [2.22–8.33] as compared to their counterparts. Similarly, participants who consume lunch daily [AOR = 1.23 95% CI 1.02–4.40] were 1.23 times more likely to overweight/obesity as compared to those who had not consumed daily Table 2 Factors affecting prevalence of obesity or overweight among office civil servants in Bahir Dar city, Ethiopia, 2020 (n = 360) Variables Category Obesity or overweight COR(95% CI) AOR(95% CI) P value Yes No Sex Female 70 112 2.088 CI (1.319, 3.306) Male 41 137 1 Monthly Income 4500 97 155 1 **Age 18–24 yrs. 3 16 0.69 CI (0.02,0.28) 0.11 CI(0.012, 0.86) 0.018 25-35yrs. 28 128 0.80 CI(0.36, 0.17) 0.15 CI(0.03,0.25) 0.001 36-45yrs. 50 94 0.19 CI(0.09, 0.42) 0.182 CI(0.07,0.47) 0.001 > 45yrs. 30 11 1 1 Injera, bread and cereal foods ≥ once a day 102 241 2.65 CI (0.99, 7.08) < once a day 9 8 1 Alcohol drink ≥ once a day 7 4 4.12 CI(1.18, 14.38) < once a day 104 245 1 **Meal frequency per day 3 meals per day 50 41 1 1 Breakfast consumption pattern Daily 109 186 18.4 CI(4.42, 76.94) Not daily 63 2 1 **Lunch consumption pattern Daily 91 179 1.77 CI (1.02,3.10) 1.230 CI (1.02,4.40) 0.001 Not daily 20 70 1 1 Dinner consumption pattern Daily 81 133 2.35 CI(1.44, 3.83) Not daily 30 116 1 **Regular physical exercise (intensive) activity at work place or at home YES 6 47 0.24 CI( 0.10, 0.59) 0.26 CI(0.09,0.73) 0.01 No 105 202 1 Moderate regular physical activity at work place or at home Yes 6 27 0.47 CI(0.18, 1.17) No 105 222 1 **Time you spent by recline or by sitting within a day (sedentary behavior) =8hrs 90 78 1 No Yes Marital Status Single 97 29 1 1 Married 140 74 1.78 (1.07–2.92) Divorced 7 4 1.91 (0.52–6.30) Widowed 5 4 2.68 (0.67–10.62) Sugar and sweet foods (cakes, chocolates, sugar, honey ≥ once a day 23 5 1 1 < once a day 226 106 2.16 (0.80–5.83) Walk or use bicycle for 10 minutes continuously Yes 229 92 0.42 (1.43–5.08) No 20 19 1 Sleeping time/day ≥ 6 hours 227 88 1 < 6 hours 22 23 0.002 Doing High intensity recreational activities Yes 36 9 1 No 213 102 1.91 Discussion The survey indicated that 30.83% (95% CI: 26.04– 35.63%) of office civil servants in a Bahir Dar city had a BMI of more than 25 kg/m2 and were overweight or obese. The result was higher than the overweight (24.1%) and obesity (19.2) prevalence in adults found from a study in Tanzania [ 16 ]. This difference may be due to socio-demographic, socio-cultural difference between the study participants and study time differences. The disparity also may be due to the study population differences as office workers are characterized by sitting for prolonged periods. A study among health Care workers (HCWs) in South Africa, where 73% were overweight or obese, and half of them had never tried to lose weight [ 4 ]. A study among college of health sciences’ employee in Ghana reported that, the prevalence of overweight and obesity was 43% and 13% respectively [ 17 ]. Another study reported that overweight/obesity among bank workers in Ghana was 55.6% [ 18 ]. The prevalence in this study was much lower compared to the above studies. The possible reasons for this disparity may be cultural, behavioral, economic and dietary habit differences between the study populations. According to this study respondents who were in the age group of 18–24 years [AOR = 9.09, 95% CI 1.16–83.33], 25–35 years [AOR = 6.66, 95% CI 4.00–33.33] and 36–45 [AOR = 5.49 95% CI [2.13–14.28] were less likely to be overweight/obesity as compared to those who were in age above 45 years, which is consistent to a study conducted in Southeast Ethiopia in 2015, being overweight was observed to increase with age advancement, 65% of those aged 51–60 years were overweight [ 19 ]. Similarly, the study result was well-matched to a study conducted on determinant factors of overweight/ obesity among federal ministry civil servants in Addis Ababa, Ethiopia, in which respondents who were age 45 years and above [AOR = 11.56, 95% CI 3.75–35.56], 35– 44 years [AOR = 11.17, 95% CI 3.89–32.06] and 25–34 [AOR = 3.08 95% CI 1.07–8.83] were more likely to be overweight/obesity as compared to those who were in age category of 24 and 18 years (39). The result was also supported in another survey conducted among adults in Hawassa city in 2015, with reference to adults 18–24 years old, the odds were three times raised among adults 45–54 (3.06, 95% CI: 1.29–7.20) and 55–64 (2.88, 95% CI: 1.06– 7.84) years of age [ 14 ]. In this study adults who took more than three times meal per day, more likely to overweight and obesity [AOR = 4.34, 95% CI [2.22–8.33] as compared to adults who took meal less than three times per day. Similarly, participants who consume lunch daily [AOR = 1.23 95% CI 1.02–4.40] were 1.23 times more likely to overweight/obesity as compared to those who had not consumed daily. Concerning meals per day, adolescents who consumed more than three meals per day had 4 times higher odds to be overweight/obese than those with less than three meals per day [AOR (95%CI) = 4.0 (1.26, 12.95) [ 20 ] which was consistent with the current study This study had contradicting result with a study which showed that having less than three meals was associated with increased odds of overweight/obesity AOR = 1.9, 95% CI; 1.12–3.28 [ 21 ]. The result is comparable to a cross-sectional study done on prevalence of overweight and obesity among office-based urban civil servants in southern nations, nationalities and peoples’ region, Ethiopia in 2015, the majorities (60.4%) typically eat three meals a day and 54.4% take an additional snack every day. Intensive regular physical activity at work place or at home was identified as a factor for overweight or obesity in this study. Participants who involved in intensive regular physical activity at work place or at home [AOR = 3.84 95% CI 1.37–11.11] were 3.84 times less likely to overweight/obesity as compared to those who had no physical activity which is parallel to a study in Tanzania that noted that those who did light intensity activities had highest prevalence of obesity (26.0%) followed by those who did moderate intensity activities (21.4%) while those who did vigorous activities had obesity prevalence of 7.6%, and to a cross sectional study among financial institution workers in Accra Metropolis where physically active respondents had a 60% reduced risk of obesity/overweight compared to those who were not physically active [ 18 ]. The result was also in line with a study in ministries civil servants in Addis Ababa, in which participants who did not involve physical activity (sport) [AOR = 2.42% 95% CI 1.36–4.30] were 2.42 times more likely to overweight/obesity as compared to those who had physical activity [ 22 ]. Time spent by recline or by sitting within a day (sedentary behavior), participants who spent less than eight hours [AOR = 10 95% CI 4.16–50.00] were 10 times less likely to overweight or obese than its counterpart which is comparable with a study in Addis Ababa showed positive association between sedentary behavior and overweight/obesity [ 21 , 22 ]. Conclusion The prevalence of overweight or obesity was high among office civil servant workers in Bahir Dar city public servant offices. As age increases there is high likely to be overweight or obese. Time spent by sitting per day, meal consumption frequency, lunch consumption frequency and high intensity regular physical exercise were found to be associated with overweight or obesity Recommendation Federal ministry of health and regional health Bureau should develop sector wise integrated occupational health program in the work place to decrease identified risk factors of overweight or obesity. Youth and sport affairs of regional bureau should strengthen mass sport programs and mobilize regular physical activities in work place. Abbreviations COR= Crude odds ratio AOR= Adjusted odds ratio CI= Confidence interval Declarations Authors’ Contributions The author confirms that they solely conducted the conceptualization, design, data collection, analysis, interpretation, drafting, and final revision of the manuscript. All work was carried out independently by the author. Acknowledgements I am very grateful to Bahir Dar University Sport academy, for their technical and financial support of this study. I would also like to thank all participants who participated in this study and their commitment in responding to our questions. References Addo PN, et al. 92015) Prevalence of obesity and overweight and associated factors among fnancial institution workers in Accra Metropolis, Ghana: a cross sectional study: BMC Res Notes. 2015; 8 (1): 599. Admasu K. (2016) Obesity government concern: The reporter 2016. Aryeetey R, Ansong J. 92011) Overweight and hypertension among college of health sciences employees in Ghana: Afr J Food Agric Nutr Dev . 2011; 11 (6). Asfaw, Abay. 2006. “The Effects of Obesity on Doctor-Diagnosed Chronic Diseases in Africa: Empirical Results from Senegal and South Africa.” Journal of Public Health Policy 27 (3): 250–64. doi: 10.1057/palgrave.jphp.3200089. Bahir Dar city civil service department 6 month report in 2020 G.C. 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Prevalence of obesity and associated risk factors among adults in Kinondoni municipal district, Dares Salaam Tanzania. Shayo and Mugusi: BMC Public Health. 2011; 11 (365). Spanier PA, Marshall SJ, Faulkner GE. (2006), Tackling the obesity pandemic a call for sedentary behavior research, Can J Public Health. 2006; 97 (3): 255-7. WHO (World health organization): The WHO Stepwise approach to chronic disease risk factor surveillance (STEPS), Switzerland; (2007). WHO (World Health Organization): The World Health Report; Reducing Risks, Promoting Healthy Life, Geneva (2002). WHO, Global recommendations on physical activity for health, 2010. WHO, Obesity and Overweight: WHO Media center. January 2015. Yoseph G, Solomon S, Balem D, Gessessew B.(2012) Nutritional status of adolescents in selected government and private secondary schools of Addis Ababa, Ethiopia, February 02, 2012 - June 28, 2012. International Journal of Nutrition and Food Sciences, Vol. 3, No. 6, 2014, pp. 504-514. 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The results of this study can be used as a reference for program planners, policymakers, researchers, and organizations to design and implement an effective prevention and control strategies and programs that could address non-communicable diseases caused by overweight and obesity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe manuscript is drawn from a full length research paper done by the Authors included in the manuscript and sponsored by Bahirdar University. Manuscript begins with introduction, in the method section (study setting and participants, measurements, data analysis, ethical clearance, patient and public involvement) are included. In the result section (demographic information, prevalence of obesity/overweight and associated risk factors of overweight or obesity) are presented. Discussion, conclusion, recommendations, acknowledgment \u0026amp; funding, Authors\u0026rsquo; Contributions are included.\u003c/p\u003e\n\u003cp\u003eThe manuscript of study tries to address a growing public health importance concern of the nation which is associated with many of the chronic diseases. Measurements of multiple variables having significance on overweight/obesity including level of physical activity were attempted to address. Although it is known that being overweight or obese brings a variety of health complications, no attempt was made to assess such issues in the study population. Recommendations for other researchers concerning issues not covered by this study are addressed for readers in the study.\u003c/p\u003e\n"},{"header":"Introduction","content":"\u003cp\u003eOverweight and obesity was defined as \u0026ldquo;abnormal or excessive accumulation of fat that may impair health\u0026rdquo; and formally recognized as a global epidemic in 1997 by WHO [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is a disorder of energy metabolism that occurs when the balance between energy intake and expenditure is disrupted. It involves body fatness or excessive adipose tissue stores that can be associated with medical or psychosocial morbidity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Body mass index (BMI) is used to classify overweight and obesity in adults commonly [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is currently estimated that as much as 20\u0026ndash;50% of urban populations in Africa are classified as either overweight or obese and that by 2025, three quarters of the obese population worldwide will be in non-industrialized countries. WHO had declared overweight as one of the top ten health risks in the world and one of the top five in developed nations [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Africa, researchers and policy makers concentration was on malnutrition and infectious diseases. However, in recent times, a sharp rise in the incidence of obesity and chronic diseases has been observed and recognized as a major public health problem in many African countries [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOverweight/obesity seems an unusual concern in Ethiopia\u0026rsquo;s public health; however, the government revealed that being overweight/obesity is emerging fast as a non-communicable public health concern [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Despite the fact that physiological, genetic and environmental factors are contributing factors for weight gain, insufficient energy expenditure due to insufficient physical activity or sitting for prolonged periods is the main physiological factor [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This sedentary lifestyle with a dietary alteration (fast food) is a vital health behavior responsible for the remarkable increase in obesity or becoming overweight [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough genetic factor plays significant role in overweight and obesity fast economic growth and development, urbanization, and changes in dietary and lifestyle patterns including the work, household, recreational, transportation, sedentary lifestyle, and physical inactivity also affects overweight and obesity. Overweight/obesity seems an unusual concern in Ethiopia\u0026rsquo;s public health; however, the government revealed that being overweight/obesity is emerging fast as a non-communicable public health concern [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePhysical inactivity is identified as the fourth leading risk factor (6%) for global mortality next to high blood pressure, tobacco use and high blood glucose level. In many countries physical inactivity levels are increasing with major implications for the general health of the community and prevalence of non-communicable diseases worldwide [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Even though, the magnitude and severity of overweight and obesity is increasing from time to time, there are only few researches conducted on the prevalence and associated factors of overweight/obesity in office civil servants. As a result, there is lack of nationally representative data on the problem. Therefore, further studies are required to design and implement prevention, control and management strategies for overweight/obesity. Hence, the present study aims to provide baseline and reference data on the prevalence and associated factors of overweight and obesity among office civil servant workers in Bahir Dar city administration.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Setting and Participants\u003c/h2\u003e \u003cp\u003eInstitution based cross-sectional study design was conducted from June 01\u0026ndash;15 /2020 among Office Public Servants in case of Bahir Dar city Administration public sectors. Bahir Dar city is located at an attitude of 1820 meters (5970ft) above sea level. The city is located approximately 578km north/north west of Addis Ababa. The city has 6 sub-cities namely; Fasilo, Tana, Atse Tewodros, Gish Abay, Belay Zeleke and Dagmawi Minilik. According to the city civil service department there were 36 civil servant offices/departments in Bahir Dar city directly accountable to the city administration and there were about 3651 (2016 male and 1645 female) civil servants who are working there [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo select study unit, ten out of thirty-six public service departments/offices namely: Mayor office, Transport, Finance and economic development, Health, House development, Social affairs, Women and children, First instance court, Civil Service and Tana sub-city departments were randomly selected. Study participants from ten offices/departments were selected by simple random sampling method after proportionally allocated to the ten offices to select required sample participants, Sample size was determined by single population proportion formula using Epi- Info version 7 software with the assumption of 95% confidence interval, 5% margin of error, and considering prevalence of overweight 47% (on a study done among office based urban civil servants in Southern nations, nationalities and peoples\u0026rsquo; region, Ethiopia) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and adding 5% nonresponse rate which provides a total sample size of 365 individuals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Measurements\u003c/h2\u003e \u003cp\u003eMost parts of the questionnaires were adapted from WHO steps instrument for chronic disease risk surveillance [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The data was collected by using semi-structured self-administered questionnaire. The questionnaire was prepared in English, translated to Amharic and then to English by language experts and finalized and administered in Amharic language which is widely spoken in the city. The data was collected on socio-demographic characteristics (sex, age, educational and marital status), and behavioral factors like alcohol consumption, dietary habits, physical activity and recreational activities. Anthropometric measurements of weight, and height were performed by using calibrated equipment and standardized techniques.\u003c/p\u003e \u003cp\u003eWeight was recorded using a portable digital weight scale with a precision of 0.5 kilograms. BMI was calculated as BMI\u0026thinsp;=\u0026thinsp;Weight (kg)/ [Height (m)2]. According to the WHO classification of BMI, Less than 18.5 consider underweight, 18.5\u0026ndash;24.9 normal weight, 25\u0026ndash;29.9 overweight and \u0026ge;\u0026thinsp;30 obese. Global Physical Activity Questionnaire developed by WHO for physical activity surveillance was used. The quality of data was ensured during collection, coding, entry and analysis. During the data collection time, adequate supervision and follow up was provided to the data collectors and were checked on 10% of the respondents.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Data Analysis\u003c/h2\u003e \u003cp\u003eData were entered into EPI DATA version 3.2 Software and analyzed by Statistical Product and Service Solutions (SPSS) version 23. Descriptive statistics using frequencies, proportions and table were used to present the study results.\u003c/p\u003e \u003cp\u003eBivariate analysis was conducted to screen the possible determinants of overweight and obesity and variables with p-values of \u0026le;\u0026thinsp;0.2 regression analysis and important variables for the objective of the study based on literature review were entered to the multivariate model and stepwise forward regression procedure was employed. Associated factors were identified using binary logistic regression model. Finally, in multi-variable binary logistic regression analysis, factors associated with overweight/obesity were identified using their Adjusted Odds Ratio (AOR) with the corresponding 95% CI. Hosmer and Lemshow goodness of fit test were used to check whether the predictors adequately explain the response variable. The model fitness was checked by Hosmer- Lemeshow test. Hosmer and Lemshow goodness of fit test was declared at p-value of 0.05. Statistical significance was considered at significance level of 5%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Ethical Clearance\u003c/h2\u003e \u003cp\u003e Prior to starting the work, the Ethical Review Committee of the Bahir Dar University approved the study proposal. The aim of the study was explained to study subjects and their values, culture, belief, religion and norms were respected. The survey forms did not include personal identifiers in order to protect confidentiality of patients. Both Written and Verbal informed consent were obtained from each participant. There was no invasive procedure performed to conduct this study, instead measuring of physical composition was performed.\u003c/p\u003e \u003cp\u003ePrivacy and confidentiality of each study participant were strictly kept and all overweight /obese civil servants were provided a brief information on overall risk factors of overweight and or obesity. All who participated in the study were acknowledged.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Patient and Public Involvement\u003c/h2\u003e \u003cp\u003eThere was no invasive procedure performed to conduct this study, instead measuring of physical composition was performed. The study participants are not labeled as patients by physicians or they are not taken as peoples with known problems by themselves and also by the society rather they are civil servants found in a city of Bahirdar. Even though they are not considered as patients the status shown from the data needs to be considered keep confidential. The survey forms did not include personal identifiers in order to protect confidentiality of participants. Both Written and Verbal informed consent were obtained from each participant. The result will be planned to disseminate through seminars organized by the civil servant office of the city. Participants will be informed about result and if they agreed intervention will be made given by in collaboration with ministry of health.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Socio-Demographic Characteristics\u003c/h2\u003e \u003cp\u003eIn this study, a total of 365 participants were recruited of them, 360 participated with overall response rate of 98.63%. From the respondents 164 (45.6%) were female. Regarding to respondent age majority of them was in the age group of (25\u0026ndash;35 years) (43.3%). More than half of respondents were educated to the level of undergraduate degree (59.7%). About 70% of respondents were paid more than 4500 Ethiopian birr (252, 70%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of respondents among office civil servants in Bahir Dar city administration, Ethiopia, 2020 (n\u0026thinsp;=\u0026thinsp;360).\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=\"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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\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\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent\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\u003eSex (N\u0026thinsp;=\u0026thinsp;360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.4\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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge (N\u0026thinsp;=\u0026thinsp;360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18-24yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25-35yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36-45yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;45yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEducational level (N\u0026thinsp;=\u0026thinsp;360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh school and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUndergraduate degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMasters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eIncome (N\u0026thinsp;=\u0026thinsp;360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2500\u0026ndash;3500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3600\u0026ndash;4500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;4500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eService year (N\u0026thinsp;=\u0026thinsp;360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 month to 5 yrs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5-10yrs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11-15yrs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;15yrs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMarital status (N\u0026thinsp;=\u0026thinsp;360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.4\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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1\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=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Associated risk Factors of Overweight or Obesity\u003c/h2\u003e \u003cp\u003eIn the bi-variable analysis age, income, Injera, bread and cereal foods, Meal frequency per day, Breakfast consumption pattern, Lunch consumption pattern, Dinner consumption pattern, Regular physical exercise (intensive activity at work place or at home), Moderate regular physical activity at work place or at home, Time you spend by recline or by sitting within a day (sedentary behavior), marital status, sugar and sweet foods, spent in sleeping within a day, doing high recreational activity and alcohol consumption were filtered.\u003c/p\u003e \u003cp\u003eIn the multivariable logistic regression analysis variables that showed statistically significant association with obesity and overweight using p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were age, Meal frequency consumption pattern, lunch frequency consumption pattern, Time you spend by recline or by sitting within a day (sedentary behavior) and regular physical exercise or intensive activity at work place or at home.\u003c/p\u003e \u003cp\u003eRespondents who were age 18\u0026ndash;24 years [AOR\u0026thinsp;=\u0026thinsp;9.09, 95% CI 1.16\u0026ndash;83.33], 25\u0026ndash;35 years [AOR\u0026thinsp;=\u0026thinsp;6.66, 95% CI 4.00\u0026ndash;33.33] and 36\u0026ndash;45 [AOR\u0026thinsp;=\u0026thinsp;5.49 95% CI [2.13\u0026ndash;14.28] were less likely to be overweight/obesity as compared to those who were in, age above 45 years. Another risk factor was adults who took more than three times meal per day, more likely to overweight and obesity [AOR\u0026thinsp;=\u0026thinsp;4.34, 95% CI [2.22\u0026ndash;8.33] as compared to their counterparts. Similarly, participants who consume lunch daily [AOR\u0026thinsp;=\u0026thinsp;1.23 95% CI 1.02\u0026ndash;4.40] were 1.23 times more likely to overweight/obesity as compared to those who had not consumed daily\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\u003eFactors affecting prevalence of obesity or overweight among office civil servants in Bahir Dar city, Ethiopia, 2020 (n\u0026thinsp;=\u0026thinsp;360)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eObesity or overweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCOR(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.088 CI (1.319, 3.306)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMonthly Income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2500\u0026ndash;3500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.178 CI(0.61, 0.514)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3600\u0026ndash;4500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.320CI (0.32, 0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;4500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e155\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e**Age\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;24 yrs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.69 CI (0.02,0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.11\u003c/b\u003e CI(0.012, 0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.018\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25-35yrs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.80 CI(0.36, 0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.15\u003c/b\u003e CI(0.03,0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36-45yrs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19 CI(0.09, 0.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.182\u003c/b\u003e CI(0.07,0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;45yrs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\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 \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eInjera, bread and cereal foods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge; once a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.65 CI (0.99, 7.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; once a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlcohol drink\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge; once a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.12 CI(1.18, 14.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; once a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e245\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e**Meal frequency per day\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;=3 meals per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24 CI(0.14, 0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.23\u003c/b\u003e CI (0.12,0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3 meals per day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41\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 \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBreakfast consumption pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDaily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.4 CI(4.42, 76.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e**Lunch consumption pattern\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDaily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.77 CI (1.02,3.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.230\u003c/b\u003e CI (1.02,4.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70\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\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDinner consumption pattern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDaily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.35 CI(1.44, 3.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot daily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e116\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e**Regular physical exercise (intensive) activity at work place or at home\u003c/b\u003e\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\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24 CI( 0.10, 0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.26\u003c/b\u003e CI(0.09,0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.01\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\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e202\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModerate regular physical activity at work place or at home\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\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.47 CI(0.18, 1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\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\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e222\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e**Time you spent by recline or by sitting within a day (sedentary behavior)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;8hrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.12 CI(0.06, 0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.10\u003c/b\u003e CI (0.02,0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;=8hrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMarital Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29\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 \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.78 (1.07\u0026ndash;2.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\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\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.91 (0.52\u0026ndash;6.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\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\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.68 (0.67\u0026ndash;10.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSugar and sweet foods (cakes, chocolates, sugar, honey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge; once a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\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 \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; once a day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.16 (0.80\u0026ndash;5.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWalk or use bicycle for 10 minutes continuously\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\u003e229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42 (1.43\u0026ndash;5.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\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\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSleeping time/day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;6 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;6 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDoing High intensity recreational 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\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\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\u003e213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe survey indicated that 30.83% (95% CI: 26.04\u0026ndash; 35.63%) of office civil servants in a Bahir Dar city had a BMI of more than 25 kg/m2 and were overweight or obese. The result was higher than the overweight (24.1%) and obesity (19.2) prevalence in adults found from a study in Tanzania [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This difference may be due to socio-demographic, socio-cultural difference between the study participants and study time differences. The disparity also may be due to the study population differences as office workers are characterized by sitting for prolonged periods. A study among health Care workers (HCWs) in South Africa, where 73% were overweight or obese, and half of them had never tried to lose weight [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. A study among college of health sciences\u0026rsquo; employee in Ghana reported that, the prevalence of overweight and obesity was 43% and 13% respectively [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Another study reported that overweight/obesity among bank workers in Ghana was 55.6% [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The prevalence in this study was much lower compared to the above studies. The possible reasons for this disparity may be cultural, behavioral, economic and dietary habit differences between the study populations.\u003c/p\u003e \u003cp\u003eAccording to this study respondents who were in the age group of 18\u0026ndash;24 years [AOR\u0026thinsp;=\u0026thinsp;9.09, 95% CI 1.16\u0026ndash;83.33], 25\u0026ndash;35 years [AOR\u0026thinsp;=\u0026thinsp;6.66, 95% CI 4.00\u0026ndash;33.33] and 36\u0026ndash;45 [AOR\u0026thinsp;=\u0026thinsp;5.49 95% CI [2.13\u0026ndash;14.28] were less likely to be overweight/obesity as compared to those who were in age above 45 years, which is consistent to a study conducted in Southeast Ethiopia in 2015, being overweight was observed to increase with age advancement, 65% of those aged 51\u0026ndash;60 years were overweight [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Similarly, the study result was well-matched to a study conducted on determinant factors of overweight/ obesity among federal ministry civil servants in Addis Ababa, Ethiopia, in which respondents who were age 45 years and above [AOR\u0026thinsp;=\u0026thinsp;11.56, 95% CI 3.75\u0026ndash;35.56], 35\u0026ndash; 44 years [AOR\u0026thinsp;=\u0026thinsp;11.17, 95% CI 3.89\u0026ndash;32.06] and 25\u0026ndash;34 [AOR\u0026thinsp;=\u0026thinsp;3.08 95% CI 1.07\u0026ndash;8.83] were more likely to be overweight/obesity as compared to those who were in age category of 24 and 18 years (39). The result was also supported in another survey conducted among adults in Hawassa city in 2015, with reference to adults 18\u0026ndash;24 years old, the odds were three times raised among adults 45\u0026ndash;54 (3.06, 95% CI: 1.29\u0026ndash;7.20) and 55\u0026ndash;64 (2.88, 95% CI: 1.06\u0026ndash; 7.84) years of age [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study adults who took more than three times meal per day, more likely to overweight and obesity [AOR\u0026thinsp;=\u0026thinsp;4.34, 95% CI [2.22\u0026ndash;8.33] as compared to adults who took meal less than three times per day. Similarly, participants who consume lunch daily [AOR\u0026thinsp;=\u0026thinsp;1.23 95% CI 1.02\u0026ndash;4.40] were 1.23 times more likely to overweight/obesity as compared to those who had not consumed daily. Concerning meals per day, adolescents who consumed more than three meals per day had 4 times higher odds to be overweight/obese than those with less than three meals per day [AOR (95%CI)\u0026thinsp;=\u0026thinsp;4.0 (1.26, 12.95) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] which was consistent with the current study This study had contradicting result with a study which showed that having less than three meals was associated with increased odds of overweight/obesity AOR\u0026thinsp;=\u0026thinsp;1.9, 95% CI; 1.12\u0026ndash;3.28 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The result is comparable to a cross-sectional study done on prevalence of overweight and obesity among office-based urban civil servants in southern nations, nationalities and peoples\u0026rsquo; region, Ethiopia in 2015, the majorities (60.4%) typically eat three meals a day and 54.4% take an additional snack every day.\u003c/p\u003e \u003cp\u003eIntensive regular physical activity at work place or at home was identified as a factor for overweight or obesity in this study. Participants who involved in intensive regular physical activity at work place or at home [AOR\u0026thinsp;=\u0026thinsp;3.84 95% CI 1.37\u0026ndash;11.11] were 3.84 times less likely to overweight/obesity as compared to those who had no physical activity which is parallel to a study in Tanzania that noted that those who did light intensity activities had highest prevalence of obesity (26.0%) followed by those who did moderate intensity activities (21.4%) while those who did vigorous activities had obesity prevalence of 7.6%, and to a cross sectional study among financial institution workers in Accra Metropolis where physically active respondents had a 60% reduced risk of obesity/overweight compared to those who were not physically active [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The result was also in line with a study in ministries civil servants in Addis Ababa, in which participants who did not involve physical activity (sport) [AOR\u0026thinsp;=\u0026thinsp;2.42% 95% CI 1.36\u0026ndash;4.30] were 2.42 times more likely to overweight/obesity as compared to those who had physical activity [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTime spent by recline or by sitting within a day (sedentary behavior), participants who spent less than eight hours [AOR\u0026thinsp;=\u0026thinsp;10 95% CI 4.16\u0026ndash;50.00] were 10 times less likely to overweight or obese than its counterpart which is comparable with a study in Addis Ababa showed positive association between sedentary behavior and overweight/obesity [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe prevalence of overweight or obesity was high among office civil servant workers in Bahir Dar city public servant offices. As age increases there is high likely to be overweight or obese. Time spent by sitting per day, meal consumption frequency, lunch consumption frequency and high intensity regular physical exercise were found to be associated with overweight or obesity\u003c/p\u003e"},{"header":"Recommendation","content":"\u003cp\u003eFederal ministry of health and regional health Bureau should develop sector wise integrated occupational health program in the work place to decrease identified risk factors of overweight or obesity. Youth and sport affairs of regional bureau should strengthen mass sport programs and mobilize regular physical activities in work place.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCOR= Crude odds ratio\u003c/p\u003e\n\u003cp\u003eAOR= Adjusted odds ratio\u003c/p\u003e\n\u003cp\u003eCI= Confidence interval\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthors\u0026rsquo; Contributions\u003c/p\u003e\n\u003cp\u003eThe author confirms that they solely conducted the conceptualization, design, data collection, analysis, interpretation, drafting, and final revision of the manuscript. All work was carried out independently by the author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI am very grateful to Bahir Dar University Sport academy, for their technical and financial support of this study. I would also like to thank all participants who participated in this study and their commitment in responding to our questions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAddo PN, et al. 92015) Prevalence of obesity and overweight and associated factors among fnancial institution workers in Accra Metropolis, Ghana: a cross sectional study: \u003cem\u003eBMC Res Notes.\u003c/em\u003e 2015; 8 (1): 599.\u003c/li\u003e\n\u003cli\u003eAdmasu K. (2016) Obesity government concern: The reporter 2016.\u003c/li\u003e\n\u003cli\u003eAryeetey R, Ansong J. 92011) Overweight and hypertension among college of health sciences employees in Ghana: \u003cem\u003eAfr J Food Agric Nutr Dev\u003c/em\u003e. 2011; 11 (6).\u003c/li\u003e\n\u003cli\u003eAsfaw, Abay. 2006. “The Effects of Obesity on Doctor-Diagnosed Chronic Diseases in Africa: Empirical Results from Senegal and South Africa.” \u003cem\u003eJournal of Public Health\u003c/em\u003e \u003cem\u003ePolicy \u003c/em\u003e27 (3): 250–64. doi: 10.1057/palgrave.jphp.3200089.\u003c/li\u003e\n\u003cli\u003eBahir Dar city civil service department 6 month report in 2020 G.C.\u003c/li\u003e\n\u003cli\u003eBiadgilign S, Mgutshini T, Haile D, Gebremichael B, Moges Y, Tilahun K. Epidemiology of obesity and overweight in sub- Saharan Africa: a protocol for a systematic review and met analysis: \u003cem\u003eBMJ Open. \u003c/em\u003e2017; 7: e017666. \u003c/li\u003e\n\u003cli\u003eDarebo et al. (2019) Prevalence and factors associated with overweight and obesity among adults in Hawassa city, southern Ethiopia: a community based cross-sectional study: \u003cem\u003eBMC Obesity\u003c/em\u003e. (2019) 6: 8: 2-10. \u003c/li\u003e\n\u003cli\u003eIloh, et al. (2011) Obesity in adult Nigerians: A study of its pattern and common primary co-morbidities in a rural Mission General Hospital in Imo state, south-eastern Nigeria: Nigerian Journal of Clinical Practice. 2011; 14 (2): 212-8.\u003c/li\u003e\n\u003cli\u003eIrene A. The overweight adolescent: Guidelines for Adolescent Nutrition Services (2005).\u003c/li\u003e\n\u003cli\u003eKassawmar A. Bogale T. and Abuhay Z. (2019) Determinant factors of overweight/ obesity among federal ministry civil servants in Addis Ababa, Ethiopia: a call for sector-wise occupational health program: \u003cem\u003eBMC\u003c/em\u003e\u003cem\u003e Research Notes.\u003c/em\u003e 2019; 449 (12): 1-6.\u003c/li\u003e\n\u003cli\u003eKautzky-Willer A, Harreiter J, Pacini G. (2016) Sex and gender differences in risk, pathophysiology and complications of type 2 diabetes mellitus: \u003cem\u003eEndocr Rev.\u003c/em\u003e 2016; 37 (3): 278–316.\u003c/li\u003e\n\u003cli\u003eMacDonald TA. (2016) Factors that influence overweight and obese men’s participation in healthy eating, exercise, and weight management programs: PhD Dissertation, 2012, Colorado State University.\u003c/li\u003e\n\u003cli\u003eMarkosY. (2019) Prevalence of overweight and obesity among office-based urban civil servants in southern nations, nationalities and peoples’ region, Ethiopia: \u003cem\u003eEthiop Med J.\u003c/em\u003e 2019, Vol. 57, No. 2: 135.\u003c/li\u003e\n\u003cli\u003eMekonnen T, Animaw W, Seyum Y. (2018) Overweight/obesity among adults in North-Western Ethiopia: a community-based cross sectional study. Arch Public Health. 2018; 76 (1): 18.\u003c/li\u003e\n\u003cli\u003eMulugeta S. (2015) Magnitude and Determinants of Overweight and Obesity among High School Adolescents in Addis Ababa, Ethiopia. \u003cem\u003eJournal of Food and Nutrition Sciences\u003c/em\u003e 2015; 3 (5): 166-173.\u003c/li\u003e\n\u003cli\u003eShayo GA, Mugusi FM. Prevalence of obesity and associated risk factors among adults in Kinondoni municipal district, Dares Salaam Tanzania. Shayo and Mugusi: \u003cem\u003eBMC Public Health.\u003c/em\u003e 2011; 11 (365).\u003c/li\u003e\n\u003cli\u003eSpanier PA, Marshall SJ, Faulkner GE. (2006), Tackling the obesity pandemic a call for sedentary behavior research, \u003cem\u003eCan J\u003c/em\u003e \u003cem\u003ePublic Health. \u003c/em\u003e2006; 97 (3): 255-7.\u003c/li\u003e\n\u003cli\u003eWHO (World health organization): The WHO Stepwise approach to chronic disease risk factor surveillance (STEPS), Switzerland; (2007).\u003c/li\u003e\n\u003cli\u003eWHO (World Health Organization): The World Health Report; Reducing Risks, Promoting Healthy Life, Geneva (2002). \u003c/li\u003e\n\u003cli\u003eWHO, Global recommendations on physical activity for health, 2010.\u003c/li\u003e\n\u003cli\u003eWHO, Obesity and Overweight: WHO Media center. January 2015.\u003c/li\u003e\n\u003cli\u003eYoseph G, Solomon S, Balem D, Gessessew B.(2012) Nutritional status of adolescents in selected government and private secondary schools of Addis Ababa, Ethiopia, February 02, 2012 - June 28, 2012. \u003cem\u003eInternational Journal of Nutrition and Food Sciences,\u003c/em\u003e Vol. 3, No. 6, 2014, pp. 504-514.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Bahir Dar University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Overweight, Obesity, Civil Servant","lastPublishedDoi":"10.21203/rs.3.rs-6861851/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6861851/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Obesity is a well-recognized risk factor for various chronic health problems. Civil servants are exposed to the sedentary lifestyle, and some of these jobs are characterized by sitting for a long period of time. Therefore, civil servants become susceptible to developing overweight/obesity, but little was researched on behalf of office civil servants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethod: Institution based cross-sectional study using Simple random sampling method was used to select 365 office civil servants working in Bahir Dar city, Northwest Ethiopia in 2020. The data was collected by using semi-structured self-administered questionnaire. The data were entered in to Epi-data and analyzed on SPSS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResult: The prevalence of overweight or obesity was 30.83% among office public servants in case of Bahir Dar city. Obesity or overweight is associated with more than three times meal per day [AOR=4.34, 95% CI [2.22–8.33], regular physical exercise or intensive activity at work place or at home [AOR= 3.84, 95% CI 1.37–11.11], recline or by sitting within a day (sedentary behavior) [AOR= 10 95% CI 4.16– 50.00].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusion and Recommendation: The prevalence of overweight or obesity was high among office civil servant workers in Bahir Dar city. Burden of overweight or obesity in this area is associated with time spent by sitting per day, meal consumption frequency, lunch consumption frequency and high intensity regular physical exercise which deserves sector wise integrated occupational health program in the work place to decrease identified risk factors of overweight or obesity.\u003c/p\u003e","manuscriptTitle":"A Prevalence and Contributing Factors of Overweight and Obesity Among Office Public Servants in Case of Bahir Dar City Administration Public Sectors, Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-11 14:53:21","doi":"10.21203/rs.3.rs-6861851/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4868d6f9-ab9a-44c1-963d-35e566375501","owner":[],"postedDate":"June 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49816441,"name":"Social Work"}],"tags":[],"updatedAt":"2025-09-03T17:08:27+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-11 14:53:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6861851","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6861851","identity":"rs-6861851","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}