Social relationships as determinants of dietary habits and intake among office-based workers: A social network analysis in southern Sri Lanka

Social relationships as determinants of dietary habits and intake among office-based workers: A social network analysis in southern Sri Lanka | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Social relationships as determinants of dietary habits and intake among office-based workers: A social network analysis in southern Sri Lanka Janaka Godevithana, Champa Jayalakshmie Wijesinghe, Millawage Supun Dilara Wijesinghe This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6415036/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Office-based workers are sedentary and have a greater risk and prevalence of non-communicable diseases (NCD). Social relationships and influences are associated with dietary behaviour and intake and can be used to change them. The Current study was conducted to assess social relationships and their associations with selected dietary behaviours and intake among office workers in a Sri Lankan setting. Office-based workers from five offices representing an entire district in southern Sri Lanka were selected as the study sample. Socio-demographic and dietary behavioural data were collected via a self-administered questionnaire. The 24-hour dietary recall was used to assess dietary intake. Relational questions with an inductive list of office workers were used to capture social relationships. Social Network Visualizer (SocNetV) software (version 3.1) created a network graph and calculated network measures. Nonparametric tests were used to assess statistical significance. This study included 139 participants (response rate, 85.3%). Social relations were not strong among office workers (in terms of density and centrality measures), and direct contact (85.6%) and telephone conversations (84.2%) were common methods of contact during and beyond office hours, respectively. Meal skipping (39.6%) and group eating (64.7%) were common. Only 5% of the workers had a healthy dietary intake. Having a degree or higher education qualification was associated with higher in-degree centrality (p = 0.02), and healthy eating was associated with higher out-degree centrality (p = 0.02). None of the other dietary variables tested showed an association with centrality measures. Office workers have weak social relationships. Unhealthy dietary behaviours are common, and dietary intake is suboptimal. Higher in-degree and out-degree centrality were associated with tertiary education and healthy eating. We recommend further studies on social relationships and their associations with dietary intake and behaviours in broader communities, focusing on personal and informal social relationships. Social relations Dietary intake Dietary behaviour Office workers Social network analysis Introduction The workforce can be defined as “people who work” ( 1 ). Nearly half of the population in European and Southeast Asian countries belong to the workforce ( 2 , 3 ). Globalisation, demographic shift, technological advancement and other economic and political forces pose many potential problems for the workforce ( 4 ). Work-related factors like changing demographic profiles (e.g., more women and older workers), employment arrangements and intensification of work demands, and increasing psychosocial hazards, in combination with workers' lifestyle, community and social factors, have resulted in several health problems for the workforce. Non-communicable diseases (NCD) have been a significant health issue in the workforce, leading to the inability to work or reduced capacity of work. Higher prevalence of NCD and its key factors (alcohol consumption, smoking, sedentary lifestyle and unhealthy diet) among the workforce were evident in many regions and countries ( 3 , 5 – 7 ). A healthy diet can be broadly defined as “a pattern of food intake that has beneficial effects on health or at least no harmful effects” ( 8 ). In contrast, an unhealthy diet can be characterized by a relatively high intake of sugar-sweetened beverages, processed food, trans- and saturated fats, added salt, and sugar and a low intake of fresh fruits, vegetables, nuts, and whole-grain products ( 9 ). A relatively high prevalence of excessive salt intake and low fruit and vegetable intake has been reported among office workers worldwide ( 3 , 5 ) and in local settings ( 10 , 11 ). Time constraints and busy schedules have been identified as factors associated with unhealthy diets among office workers (Bruhn 1999; Devine et al. 2009). An individual’s diet and dietary practices depend not solely on choices resulting from motivation and self-control. The surrounding social and physical environment plays a significant role in one’s diet and dietary practices ( 14 ). Job-related, environmental, and social factors can influence eating behaviour ( 15 ). Social influences can affect healthy eating, and social norms can significantly affect food selection and intake. Therefore, social contexts and relationships need to be carefully investigated to address changes in dietary behaviour ( 15 ). Furthermore, a qualitative study conducted among university students revealed that their dietary practices are influenced by peer pressure, social support and social norms and that beliefs can significantly affect their choice of what to eat and how much to eat ( 16 ). People in the surrounding community influence an individual’s food choices differently. Those who have a greater influence on the opinions, attitudes, beliefs, motivations, and behaviours of others are defined as opinion leaders ( 17 ). Opinion leaders share several peculiar socio-demographic characteristics, such as the degree of exposure to mass media, social participation, social and economic status, and the propensity for innovation ( 17 ). A study conducted among university students revealed that popular students tend to eat healthily and thus can influence others to do so ( 18 ). Moreover, opinion leaders have been used as promoters of healthy behaviour in many successful health behaviours change projects, including the North Karelia Project ( 19 ). Thus, identifying persons who can significantly influence others and understanding such individuals’ involvement in promoting healthy behaviour will benefit the success of health interventions. Social network analysis (SNA) can quantify the social relationships that exist between individuals or agencies of interest, and at the same time, it can qualitatively describe or graphically present the structure of social relationships ( 20 ). Thus, it can provide a quantitative and qualitative understanding of the social relationships among people and agencies by measuring the density and centrality of these relationships. Density refers to the number of links within a social network relative to all possible links, and it is a measurement of the closeness among network members. Centrality measures the interconnectedness among network members at the individual level ( 21 ). Centrality measures how important a member is to the network. A member with a higher centrality indicates that the member plays a key role in the network ( 21 ). The degree centrality measures the number of connections that a member has. The closeness centrality measures the shortest distance between two members. Higher closeness centrality indicates a close connection between two members. Betweenness centrality measures the mediating role of network members. It shows the shortest links between other members through the members of interest. A higher betweenness centrality results in a greater influence on the information or command flow within the network ( 22 ). These measurements provide an understanding of community social networks and network members' social connectedness (centrality). Such information is important for planning, implementing, monitoring and evaluating behaviour change interventions and programmes ( 21 ). Sustainable development goals (SDG) three and eight are directly related to health and the workforce ( 23 ). A healthy workforce is a key requirement for economic development and is the baseline for achieving most SGD targets. Furthermore, the workforce represents a vast majority of the population. In Sri Lanka, workforce participation was 52.3% in 2019 ( 24 ). More than half (57.9%) of the working population is formally employed, and 14.9% is employed in the public sector. According to the 2016 census, there are approximately 1.1 million employees in the public and semi-government sectors ( 25 ). Nearly half of the public and semi-governmental sector workers are office-based clerical workers who are sedentary at work. This makes them vulnerable to non-communicable diseases (NCD), and a higher prevalence of NCD has been noted in the Sri Lankan workforce ( 24 ). Furthermore, they are less accessible to health services outside office hours, as most preventive health services are limited to office hours. Workplace-based interventions effectively reduce NCD risk factors ( 26 , 27 ), as a homogenous group of people with similar risk factors are gathered in one place and tend to spend more than one-third of their day in offices. It is well documented that social ties and network characteristics can influence the effectiveness of behaviour change interventions. However, SNA and the effects of social relationships on health-related behaviours have not been adequately assessed in the local and regional context. The studies on the use of SNA data for understanding dietary behaviours and designing health interventions are minimal, even in global literature. Therefore, this study aimed to assess social relationships (as per network characteristics) and their associations with selected dietary behaviours and dietary intake among office workers in southern Sri Lanka. The current study will fill the research gap concerning the effects of social relationships on dietary behaviour and intake in the country and pave the way for further studies in this area. On the other hand, these research findings will enrich the global literature with evidence from a developing country in Asia. Methods Study setting This study was conducted in selected government offices in Galle District, Southern Sri Lanka. There are 78 government offices in the district. Five offices with more than 20–40 sedentary workers were purposefully selected to represent the district. Workers performing office-based clerical and administrative work were categorized as sedentary. Being at the office during the total working time was considered a supporting characteristic for assessing social relationships. Study participants and sampling procedure Development officers (DO), management assistants (MA), and administrative and management officers were considered sedentary workers and were recruited for the study. Workers who engaged in physical exertion during their duty hours by the nature of their work were excluded. An exhaustive list of government offices with the respective numbers of sedentary workers was prepared, and offices with 20–40 workers were shortlisted (n = 26). Five divisional secretariat offices were purposively selected from the shortlisted offices to ensure representation of all geographical areas of the district. They were Akmeemana (n = 23), Benthota (n = 31), Elpitiya (n = 29), Niyagama (n = 33) and Thawalama (n = 23). Study instruments and data collection Data on socio-demographic characteristics, health and work-related factors, and dietary practices were collected via a pretested, self-administered (survey) questionnaire (Supplementary file I). The participants were informed in advance to produce any previous clinical records (investigation reports, clinic records, etc.) at the time of data collection to verify health-related data. The weight and height of the participants were measured by trained data collectors adhering to the standard procedures described in the European Health Examination Survey (EHES) ( 28 ), and body mass index (BMI) was calculated. A trained medical officer obtained the dietary intake data for a typical office day via 24-hour dietary recall, which was supplemented by a picture guide to determine portion sizes. A computer software prepared specifically for the study was used to calculate the number of servings consumed from each food group based on the serving sizes described in the Food Based Dietary Guidelines (FBDG) for Sri Lankans − 2011( 29 ). Healthy dietary intake was defined as adherence to the number of servings recommended in the FBDG for Sri Lankans for more than three food groups, including cereal and cereal-based foods, fruits, and vegetables, with one or no unhealthy food per day. A social network survey questionnaire was used to collect data on the participants' social relationships. Information/advice seeking was considered a social connection within the office, and the participants were asked the following questions. Name five persons at the office from whom you seek information or advice on your official or personal matters. Arrange them from the most frequent to the least frequent contact. Name five persons at the office seeking information or advice from you. Arrange them from the most frequent to the least frequent contact. The main questions (Nos. 1 and 2) identified the presence of social relations, and the two branching questions (1a and 2a) assessed their magnitude and weight. A list of all workers in the respective offices was provided to answer the above questions, and participants were allowed to add any co-workers who were not included in the list. Statistical analysis Sample characteristics were described under socio-demographic, health, and work-related factors. The independent variables are categorized as shown in Table 5 . A directed and weighted network matrix was prepared for each office using the participants’ responses to the social network survey questions. Social Network Visualizer (SocNetV) software (version 3.1) was used to create the network graph and calculate network measures. Degree centrality and betweenness centrality were calculated for each individual (node) in the network, and density was calculated for the whole network. Non-parametric tests (Mann-Whitney U test and Kruskal-Wallis test) were used to assess the statistical significance of the observed associations between network measures and other study variables at a probability level of 0.05. The analyses were performed using Statistical Package for Social Sciences (SPSS) software. Ethical and administrative clearance This study adhered to the World Medical Association Declaration of Helsinki on ethical principles for medical research involving human subjects. Ethical approval for the study was obtained from the Ethics Review Committee, Faculty of Medicine, University of Ruhuna (Registration No. 2020/P/105). Administrative approval was obtained from all the relevant authorities (District Secretary, Galle District, and Regional Director of Health Services, Galle District). Informed written consent was obtained from all participants prior to data collection. Workers identified as having health issues were referred to the nearest healthcare facility with their consent. Results A total of 139 office workers participated in this study (response rate: 85.3%). The mean age of the participants was 39 (SD = 8) years, and the ages ranged from 26 to 59 years. Half of the participants (50.0%) were in the 30–39 years age group, and the vast majority (80.4%) were female. Most of the participants (93.5%) were educated up to the General Certificate of Education (GCE) (Advanced Level) or above. Nearly three-fourths of the participants (75.5%) belonged to the clerical and supportive workers category, and the remaining participants were from the managerial, professional, technical, and associate worker categories. Table 1 summarizes the socio-demographic characteristics of the participants. Table 1 Socio-demographic characteristics of the participants Characteristics Number Frequency (%) Age* < 30 years 14 11.7 30–39 years 60 50.0 40–49 years 27 22.5 ≥ 50 years 19 15.8 Sex** Female 111 80.4 Male 27 19.6 Highest educational qualification** Passed GCE Ordinary Level 9 6.5 Passed GCE Advanced Level 55 39.9 Tertiary education 74 53.6 Marital status Unmarried 19 13.7 Legally married 118 84.9 Divorced/Widowed 2 1.4 Number of living children None 32 23.0 1 34 24.5 2 49 35.3 3 or more 24 17.2 Current post held Managerial posts 14 10.1 Professionals 1 0.7 Technical and associate officers 19 13.7 Clerical and supportive officers 105 75.5 Time taken to travel for work (in minutes) 60 minutes 12 8.6 Method of transport On foot 7 5.0 Public transport 70 50.4 Private vehicle 62 44.6 *n = 120, 19 missing/**n = 138, 1 missing/***n = 516, 2 missing GCE – General Certificate of Education Nearly two-thirds of the participants (63.3%) consumed at least one snack daily, and a significant percentage (64.7%) of office workers had meals in groups. Meal skipping was common among office workers because of their workload and external or internal meetings. Almost all the participants consumed food prepared at home as their main meal (breakfast, lunch, and dinner). Among the 88 participants who consumed snacks, only seven (8.0%) reported having homemade snacks, while 60 (68.2%) of participants had snacks prepared elsewhere (office canteen or outside food stalls). However, 21 (23.8%) participants did not report the source of their snacks. Table 2 describes the participants’ dietary behaviours. Table 2 Distribution of selected dietary behaviours among the participants Characteristics Number Frequency (%) Number of snacks consumed per day* 0 51 36.7 1 67 48.2 2 or more 21 15.1 Having meals in groups Yes 90 64.7 No 49 35.3 Meal skipping None 84 60.4 One or more meals per week 55 39.6 * n = 88, 51 missing The overall dietary intake of the office workers was not satisfactory, and only 5% of the participants met the FBDG recommendation for more than three food groups, including cereal and cereal-based foods, fruits, and vegetables, with one or no unhealthy food per day. However, most met the recommended number of daily servings for cereal-based products and “fish, meat, and pulses” food groups. Interestingly, fruit and vegetable intake was suboptimal, dairy food intake was minimal, and none of the participants consumed nuts or seeds. Table 3 shows the dietary intake of office workers according to the food groups described in FBDG for Sri Lankans. Table 3 The dietary intake of office workers Food group Number of servings consumed Number of servings recommended in FBDG Number (%) having recommended minimum number of servings Mean (SD) Median (IQR) Cereal based products 6.0 (2.3) 5.7 (3.1) 6–7 69.1 Vegetables 2.8 (1.7) 2.5 (1.8) 3–5 25.9 Fruits 0.6 (0.8) 0.0 (1.0) 2–3 10.8 Fish, meat, pulses 3.4 (1.7) 3.3 (2.6) 1–2 79.9 Dairy products 0.7 (0.9) 0.5 (1.0) 3–4 3.6 Nuts and seeds 0.0 (0.1) 0.0 (0.0) 2–4 0.0 Unhealthy foods 1.9 (1.4) 2.0 (1.0) Recommended to have sparingly 43.9* *Having none or one serving of unhealthy foods per day Among the participants. interpersonal relationships were noted both during and beyond office time. However, 41 (31.7%) workers claimed they did not have relationships with coworkers beyond office time. Interestingly, direct or in-person contact was the most common method of contact during office hours, whereas telephone calls were the most common method of contact beyond office hours. Emails, SMS, and social media were used somewhat in social relationships. The density of social networks in offices was low (Akmeemana – 0.0434, Benthota – 0.0459, Elpitiya – 0.0490, Niyagama 0.0392), except for one office (Thawalama – 0.1708) (Supplementary file II). This showed fewer connections between office workers. Similarly, the results revealed low in- and out-degree centralities among the participants, confirming low social relations within most offices. On the other hand, relatively high betweenness centrality also highlighted the low levels of social relations among participants. Notably, all centrality measures showed a skewed distribution. While out-degree centrality showed positive skewness, in-degree and betweenness centrality showed negatively skewed distributions. Table 4 summarizes the measures of degree centrality and betweenness centrality. Table 4 Summary measures for centrality in social relationships among office workers Network measurement Mean (SD) Median (IQR) In-degree centrality (actual) 9.0 (9.3) 6.0 (9.0) In-degree centrality (percentage) 2.4 (2.5) 1.8 (2.8) Out-degree centrality (actual) 13.3 (5.0) 15.0 (0.0) Out-degree centrality (percentage) 3.5 (1.4) 3.7 (1.2) Betweenness centrality (actual) 91.3 (124.1) 44.0 (115.0) Betweenness centrality (percentage) 4.6 (7.1) 1.9 (6.6) Having a tertiary education was significantly associated with higher in-degree centrality, whereas having a healthy diet was significantly associated with higher out-degree centrality. However, betweenness centrality was not associated with any of the variables assessed. Socio-demographic variables such as marital status, number of children, and worker type failed to show a statistically significant association with any centrality measure. Dietary behaviours, such as skipping meals and having snacks, were not associated with any centrality measures. Table 5 summarizes the statistical analysis results assessing the associations between centrality measures, sociodemographic variables, and dietary habits. Table 5 Associations of centrality measures with the socio-demographic variables and dietary habits of the office workers Characteristic In-degree centrality Out-degree centrality Betweenness centrality Median p value Median p value Median p value Had tertiary education Yes 8.0 0.02 13.3 0.7 58.5 0.2 No 5.0 13.2 39.0 Ever married Yes 6.5 0.7 13.1 0.8 44.0 0.8 No 5.0 14.1 50.0 Clerical worker Yes 7.0 0.4 13.4 0.9 51.0 0.3 No 5.0 12.8 34.8 Number of children No children 5.0 0.07 13.7 0.08 61.5 0.7 One child 4.5 13.8 37.8 Two or more children 9.0 12.8 44.0 Number of snacks per day None 6.0 0.8 12.6 0.5 47.0 0.5 One 8.0 13.4 53.0 Two or more 7.0 14.3 20.0 Group eating Yes 1.9 0.1 3.7 0.9 2.1 0.9 No 1.5 3.7 1.7 Meal skipping Yes 6.0 0.3 13.4 0.3 40.0 0.2 No 8.0 12.9 54.3 Having a healthy diet Yes 7.0 0.9 16.3 0.02 118.0 0.1 No 6.0 13.1 41.0 Discussion The current study assessed social relationships (as per network characteristics) and their associations with selected dietary behaviours and dietary intake among office workers at five offices in the Galle district. The findings revealed that social relations are not strong among office workers (in terms of density and centrality measures), and direct contact and telephone conversations are common methods of contact during office hours and beyond office hours, respectively. Furthermore, this study highlighted the presence of undesirable dietary habits (meal skipping and group eating) and suboptimal dietary intake among office workers. A degree or higher education qualification was associated with higher in-degree centrality, whereas healthy eating was associated with higher out-degree centrality. None of the other variables tested showed associations with centrality measures. This discussion focuses mainly on the significance of the above findings with respect to the literature and local context, their implications, and recommendations for further research on social relationships, dietary behaviours, and intake. Nearly three-fourths of the participants (72.5%) were in the 30–49 age group. Therefore, the sample was composed of relatively young participants, which needs to be considered when interpreting the study findings. The majority (80.4%) of the study participants were female. Although the Sri Lankan workforce is male dominated, its composition and sex distribution can vary across different sectors ( 25 ). Similar findings regarding sex distributions have been reported in a previous study conducted in the Colombo District (Swarnamali et al., 2017). Most workers (93.5%) were educated at the advanced GCE level or had completed tertiary education. Development officers and management assistants require a degree and GCE Advanced Level educational qualifications. Swarnamali et al. (2017) reported similar education levels among public sector workers in the Colombo District. The percentages of participants using public transport and walking to reach the workplace (50.4% and 5.0%, respectively) are consistent with data from the 2016 census of public sector workers, where 46.7% used public transport and 5.7% walked to reach the office ( 25 ). This indicates the representativeness of our study sample of office workers in a sedentary working environment in the local context. Interestingly, nearly 75% of the workers belonged to the clerical and supportive worker category, whereas the rest belonged to the manager, professional, and technical officer categories. We believe that this composition ensured the effective capturing of social relations because officers in the same category will have more personal relations among them. Personal relations are more influential on personal behaviours than official relations with different categories. Unhealthy snacking was common among office workers in this study, with 63.3% consuming one or more snacks daily. Several studies have highlighted the increased snack consumption among office workers in Southeast Asia and globally ( 30 – 33 ). Consistent with similar studies ( 30 , 34 ), nearly 40% of the participants reported skipping meals. Nearly two-thirds (64.7%) of the participants reported eating in groups. Previous studies have highlighted group eating as a factor associated with high calorie intake ( 35 , 36 ) and unhealthy dietary intake ( 37 ), though only a few studies have focused on social relationships and group eating ( 38 , 39 ). However, we believe that group eating shows more significant social ties within groups, and further studies are needed to evaluate its influence on dietary intake. The current study reported suboptimal dietary intake with low fruit and vegetable intake and high unhealthy food intake. Swarnamali et al. (2017) reported low fruit and vegetable and high added sugar intake among Sri Lankan office workers. Low fruit and vegetable intake has also been highlighted among the general Sri Lankan population in the STEPs survey ( 40 ). Furthermore, Swarnamali et al. (2017) reported high starchy food intake, whereas the current study reported only a marginally high intake. A marginally high consumption of carbohydrates among public sector workers was evident in another large-scale study conducted in Sri Lanka ( 11 ). Network density was low in all offices, indicating weak social relationships among office workers. There were hardly any studies that assessed network density alone in office workers. Two studies have reported higher density among office workers and have highlighted that a greater network density is associated with greater worker performance ( 41 ) and job satisfaction ( 42 ). A study among healthcare workers in Canada revealed low-density networks among healthcare workers seeking information. Furthermore, the same study highlighted clustering within organizational divisions ( 43 ). The reported low density may have resulted from multiple functional divisions within an office. However, a study of nurses revealed that a higher number of staff members resulted in a lower density ( 42 ). We believe the offices with reasonably high staff numbers and internal functional divisions included in the current study resulted in low-density values. The current study reported higher betweenness centrality than in- and out-degree centrality. This is explained by the low-density networks and functional divisions within the offices. Relations are limited to functional divisions, and most office workers appear as mediators within the shortest path connecting two workers. Higher median centrality (in-degree, out-degree, and betweenness) values were associated with tertiary education among the office workers. However, only in-degree centrality was significantly associated with tertiary education. Multiple studies have reported a positive correlation between education level and degree centrality ( 44 – 46 ). Notably, females with higher educational levels had a higher degree of centrality (Ajrouch et al. 2005; Fang and Zhang 2014). Thus, the higher percentage of females in the current study would also explain the higher centrality in the tertiary education group. There is conflicting evidence regarding the association between the number of children and degree centrality measures. The number of children was not significantly associated with centrality measures in this study. In contrast, a study conducted in Israel showed that centrality measures could vary by gender and having children or parenting reduces centrality among females, whereas males have an inverse association ( 47 ). The same study also highlighted that job category can change the direction of such associations. Higher centrality has been reported for parenting males and females in higher job categories ( 47 ). A large-scale study conducted on workers in 11 countries concluded that having children could increase the degree of centrality in both men and women ( 48 ). The job category was also identified as an important determinant of degree centrality. This is explained by the fact that the higher the category is, the more opinions you will be asked for, and vice versa ( 44 , 46 ). However, this study failed to show an association between occupation and centrality measures. This finding must be interpreted cautiously because the low number of workers in categories other than clerical and supportive workers can distort the association. Several studies showed associations between social relationships, dietary behaviour, and dietary intake. Most such studies have been conducted among adolescents, where peer influence is more prevalent regarding dietary intake and behaviour. A few systematic reviews have concluded that dietary intake and behaviour are associated with social relationships ( 49 – 51 ). However, none of these studies have assessed the associations between an individual’s social network characteristics and dietary intake and behaviour. The present study fills this void by assessing the associations between participants’ social network characteristics, such as centrality, and their dietary intake and behaviour. A higher out-degree centrality was associated with healthier dietary intake. This implies that workers who are reached by others have healthier dietary intake. However, no other network measurements showed associations with dietary intake or behaviours such as meal skipping and group eating. This should be interpreted with caution because office workers with a healthy dietary intake accounted for only 5% of the sample. Although the frequent consumption of snacks and other unhealthy behaviours were found to be associated with social networks in adolescents, the current study failed to establish such associations with network measurements. We believe that the age composition and the nature of relationships (mostly official and non-influential in personal decision-making) have contributed to these contrasting findings. Considering their geographical distribution, the offices were selected to represent the entire district, and workers involved only in office-based work were included in the study. Therefore, the study sample is reasonably representative of the office-based workers in the Galle District, ensuring the external validity of the study. Moreover, the current study focused on participants’ characteristics within networks and their associations with dietary intake and behaviour - a phenomenon which has not been widely studied in literature. Despite the above strengths, this study has several limitations. First, we observed that the network captured through relational questions was more focused on official relationships rather than personal or emotional relationships that can alter diet and dietary behaviour. Furthermore, we did not consider subgroups and clustering within the office in the data analysis, as it was outside the scope of the current study. Conclusion and recommendations In conclusion, office workers had weak social relationships; direct contact and telephone calls were the main contact methods. Unhealthy dietary behaviours (snacking, group eating, and meal skipping) were common, and dietary intake was suboptimal, with low vegetable and fruit intake. Higher in-degree centrality was associated with the office workers' higher educational status, and higher out-degree centrality was associated with healthy eating. We recommend further studies on social relationships and their associations with dietary intake and behaviours in broader community settings, focusing more on personal and informal social relationships that can influence health behaviour and behaviour change. In addition, we believe that longitudinal studies on social relationships and dietary behaviour will firmly establish the associations identified in the current study. Further, we recommend including workers with higher out degree centrality and healthy dietary intake as changing agents in health promotion interventions in office settings. Abbreviations BMI Body Mass Index CI Confidence Interval DALY Disability Adjusted Life Years DO Development Officer EHES European Health Examination Survey FBGD Food Based Dietary Guidelines FBDG-SL Food Based Dietary Guidelines for Sri Lankans GBD Global Burden of Disease GCE General Certificate of Education IQR Inter Quartile Range MA Management Assistant NCD Non-Communicable Disease SD Standard Deviation WHO World Health Organization YLL Years of Life Lost Declarations Ethics approval and consent to participate. The authors declare that Ethical approval for the study was obtained from the Ethics Review Committee, Faculty of Medicine, University of Ruhuna (Registration No. 2020/P/105). Administrative approval was obtained from the District Secretariat Galle District and Regional Director of Health Services-Galle District. Informed written consent was obtained from all office workers before data collection. Workers identified with problems were referred to the nearest healthcare facility with consent. The study was conducted while adhering to the World Medical Association Declaration of Helsinki on ethical principles for medical research involving human subjects. Consent for publication In the current study consent for publication is not applicable as no individual-level data with identification was included in the manuscript. Availability of data and materials The datasets used and/or analysed during the current study are available from the following link. https://drive.google.com/drive/folders/1AnydiyNCPgHTf4MXty9E73_m_JTtSpCm?usp=sharing Competing interests The authors declare that they have no competing interests. Funding The study was self-funded by the corresponding author. Author contributions JG planned the research project, data collection, statistical analysis and manuscript writing. CJW and MSDW provided technical guidance and supervised the research project. All authors read and approved the manuscript. Acknowledgment Authors acknowledge the District Secretary-Galle District and the Chief Secretary-Sothern Province for granting administrative approval for the study and all Divisional Secretaries and Heads of local authorities supporting the project. Dr. Sithara Kulathunga, Dr. Sulekha Peellage and Dr. Isuri Sandunika are acknowledged for their contribution in data collection. References Cambridge University Press & Assessment. Cambridge English Dictionary and Thesaurus [Internet]. 2025 [cited 2025 Apr 7]. Available from: https://dictionary.cambridge.org/dictionary/ Sakowski P, Marcinkiewicz A. Health promotion and prevention in occupational health systems in Europe. Int J Occup Med Environ Health [Internet]. 2019 Jun 14 [cited 2022 Jul 27];32(3):353–61. Available from: http://ijomeh.eu/Health-promotion-and-prevention-in-occupational-health-systems-in-Europe,97178,0,2.html Sukumar GM, Joseph B. 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Degree Centrality, Betweenness Centrality, and Closeness Centrality in Social Network. 2017 [cited 2025 Jan 7]; Available from: https://www.researchgate.net/publication/316452659_Degree_Centrality_Betweenness_Centrality_and_Closeness_Centrality_in_Social_Network United Nations Development Programme. Sustainable Development Goals [Internet]. 2025 [cited 2025 Apr 4]. Available from: https://www.undp.org/sustainable-development-goals Department of Census, Statistics. labour force data [Internet]. Department of Census and Statistics, Battaramulla: Department of Census and Statistics; 2020. Available from: http://www.statistics.gov.lk/samplesurvey/LFS_Annual%20Report_2017.pdf Department of Census, Statistics. Census of Public and Semi Government Sector Employment – 2016 [Internet]. 1st ed. Colombo, Sri Lanka: Department of Census and Statistics, Ministry of National Policies and Economic Affairs; 2016 [cited 2024 Jun 13]. Available from: https://www.statistics.gov.lk/Resource/en/PublicEmployment/census_reports/FinalReport2016.pdf Chandrasiri A, Dissanayake A, De Silva V. Health promotion in workplaces strategy for modification of risk factors for Non Communicable Diseases (NCDs): A practical example from Sri Lanka. Work. 2016 Jan 1;55(2):281–4. Shrestha A, Karmacharya BM, Khudyakov P, Weber MB, Spiegelman D. Dietary interventions to prevent and manage diabetes in worksite settings: a meta-analysis. J Occup Health [Internet]. 2018 [cited 2022 Feb 10];60(1):31. Available from: /pmc/articles/PMC5799099/ Tolonen H, editor. EHES Manual. Part B. Fieldwork procedures. 2nd ed. Helsinki, Finland: National Institute for Health and Welfare; 2016. Nutrition Division Ministry of Health, editor. Food Based Dietary guidelines for Sri Lankans. 2nd ed. Colombo: Nutrition Division Ministry of Health; 2011. Hyun Park S, Ji Lee E, Ja Chang K. Dietary Habits and Snack Consumption Behaviors according to Level of Job Stress among 20- to 30-year old Office Workers in the Seoul Metropolitan Area. Journal of the Korean Society of Food Culture [Internet]. 2020 [cited 2025 Feb 10];35(2):143–55. Available from: https://doi.org/10.7318/KJFC/2020.35.2.143 Thike TZ, Saw YM, Lin H, Chit K, Tun AB, Htet H, et al. Association between body mass index and ready-to-eat food consumption among sedentary staff in Nay Pyi Taw union territory, Myanmar. BMC Public Health [Internet]. 2020 Feb 10 [cited 2025 Feb 10];20(1):1–10. Available from: https://link.springer.com/articles/10.1186/s12889-020-8308-6 Baskin E, Gorlin M, Chance Z, Novemsky N, Dhar R, Huskey K, et al. Proximity of snacks to beverages increases food consumption in the workplace: A field study. Appetite. 2016 Aug 1;103:244–8. Barnes TL, French SA, Harnack LJ, Mitchell NR, Wolfson J. Snacking Behaviors, Diet Quality, and Body Mass Index in a Community Sample of Working Adults. J Acad Nutr Diet. 2015 Jul 1;115(7):1117–23. Shin WY, Kim JH. Use of workplace foodservices is associated with reduced meal skipping in Korean adult workers: A nationwide cross-sectional study. PLoS One [Internet]. 2020 Dec 1 [cited 2025 Feb 10];15(12):e0243160. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0243160 Wansink B. Environmental factors that increase the food intake and consumption volume of unknowing consumers. Annu Rev Nutr [Internet]. 2004 [cited 2022 Jul 29];24:455–79. Available from: https://pubmed.ncbi.nlm.nih.gov/15189128/ Hetherington MM, Anderson AS, Norton GNM, Newson L. Situational effects on meal intake: A comparison of eating alone and eating with others. Physiol Behav [Internet]. 2006 Jul 30 [cited 2022 Jul 23];88(4–5):498–505. Available from: https://pubmed.ncbi.nlm.nih.gov/16757007/ Godevithana J, Wijesinghe CJ, Wijesinghe MSD. Prevalence and determinants of healthy and balanced diet among office workers in a sedentary working environment: evidence from Southern Sri Lanka. BMC Public Health [Internet]. 2024 Dec 1 [cited 2025 Feb 11];24(1). Available from: https://pubmed.ncbi.nlm.nih.gov/39696073/ Herman CP. The social facilitation of eating. A review. Appetite. 2015 Mar 1;86:61–73. Clendenen VI, Herman CP, Polivy J. Social Facilitation of Eating Among Friends and Strangers. Appetite. 1994 Aug 1;23(1):1–13. Ministry of Health Nutrition and Indigenous Medicine. Non Communicable Disease Risk Factor Survey Sri Lanka 2015 [Internet]. 1st ed. Colombo: Ministry of Health, Nutrition and Indigeneous Medicine; 2017. Available from: https://www.who.int/ncds/surveillance/steps/STEPS-report-2015-Sri-Lanka.pdf Sparrowe RT, Liden RC, Wayne SJ, Kraimer ML. Social Networks and the Performance of Individuals and Groups. Academy of Management Journal. 2001 Apr;44(2):316–25. van Beek AP, Wagner C, Spreeuwenberg PP, Frijters DH, Ribbe MW, Groenewegen PP. Communication, advice exchange and job satisfaction of nursing staff: a social network analyses of 35 long-term care units. BMC Health Serv Res [Internet]. 2011 [cited 2025 Feb 13];11. Available from: http://www.biomedcentral.com/1472-6963/11/140 Yousefi-Nooraie R, Dobbins M, Brouwers M, Wakefield P. Information seeking for making evidence-informed decisions: a social network analysis on the staff of a public health department in Canada. BMC Health Serv Res [Internet]. 2012 [cited 2025 Feb 13];12. Available from: http://www.biomedcentral.com/1472-6963/12/118 Ajrouch KJ, Blandon AY, Antonucci TC. Social networks among men and women: The effects of age and socioeconomic status. Journals of Gerontology - Series B Psychological Sciences and Social Sciences. 2005;60(6). Liu Y, Ipe M. How Do They Become Nodes? Revisiting Team Member Network Centrality. J Psychol. 2010 Apr 1;144(3):243–58. Fang R, Zhang Z. A Meta-Analysis on Women’s Social Network Position: Does Education Help? 74th Annual Meeting of the Academy of Management, AOM 2014. 2014;1382–7. Snir R, Harpaz I, Ben-Baruch D. Centrality of and Investment in Work and Family Among Israeli High-Tech Workers. Cross-Cultural Research. 2009 Nov;43(4):366–85. Sweet S, Sarkisian N, Matz-Costa C, Pitt-Catsouphes M. Are women less career centric than men? Structure, culture, and identity investments. Community Work Fam. 2016 Aug 7;19(4):481–500. Zhang S, de la Haye K, Ji M, An R. Applications of social network analysis to obesity: a systematic review. Obesity Reviews [Internet]. 2018 Jul 1 [cited 2025 Feb 15];19(7):976–88. Available from: https://onlinelibrary.wiley.com/doi/full/10.1111/obr.12684 Fletcher A, Bonell C, Sorhaindo A. You are what your friends eat: systematic review of social network analyses of young peopleâï¿¿TMs eating behaviours and bodyweight. J Epidemiol Community Health (1978) [Internet]. 2011 [cited 2025 Feb 15];65(6). Available from: https://hal.science/hal-00625559v1 Sawka KJ, McCormack GR, Nettel-Aguirre A, Swanson K. Associations between aspects of friendship networks and dietary behavior in youth: Findings from a systematized review. Eat Behav. 2015 Aug 1;18:7–15. Additional Declarations No competing interests reported. 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Nearly half of the population in European and Southeast Asian countries belong to the workforce (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Globalisation, demographic shift, technological advancement and other economic and political forces pose many potential problems for the workforce (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Work-related factors like changing demographic profiles (e.g., more women and older workers), employment arrangements and intensification of work demands, and increasing psychosocial hazards, in combination with workers' lifestyle, community and social factors, have resulted in several health problems for the workforce. Non-communicable diseases (NCD) have been a significant health issue in the workforce, leading to the inability to work or reduced capacity of work. Higher prevalence of NCD and its key factors (alcohol consumption, smoking, sedentary lifestyle and unhealthy diet) among the workforce were evident in many regions and countries (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e–\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA healthy diet can be broadly defined as “a pattern of food intake that has beneficial effects on health or at least no harmful effects” (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In contrast, an unhealthy diet can be characterized by a relatively high intake of sugar-sweetened beverages, processed food, trans- and saturated fats, added salt, and sugar and a low intake of fresh fruits, vegetables, nuts, and whole-grain products (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). A relatively high prevalence of excessive salt intake and low fruit and vegetable intake has been reported among office workers worldwide (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) and in local settings (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Time constraints and busy schedules have been identified as factors associated with unhealthy diets among office workers (Bruhn 1999; Devine et al. 2009).\u003c/p\u003e \u003cp\u003eAn individual’s diet and dietary practices depend not solely on choices resulting from motivation and self-control. The surrounding social and physical environment plays a significant role in one’s diet and dietary practices (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Job-related, environmental, and social factors can influence eating behaviour (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Social influences can affect healthy eating, and social norms can significantly affect food selection and intake. Therefore, social contexts and relationships need to be carefully investigated to address changes in dietary behaviour (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Furthermore, a qualitative study conducted among university students revealed that their dietary practices are influenced by peer pressure, social support and social norms and that beliefs can significantly affect their choice of what to eat and how much to eat (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePeople in the surrounding community influence an individual’s food choices differently. Those who have a greater influence on the opinions, attitudes, beliefs, motivations, and behaviours of others are defined as opinion leaders (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Opinion leaders share several peculiar socio-demographic characteristics, such as the degree of exposure to mass media, social participation, social and economic status, and the propensity for innovation (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). A study conducted among university students revealed that popular students tend to eat healthily and thus can influence others to do so (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Moreover, opinion leaders have been used as promoters of healthy behaviour in many successful health behaviours change projects, including the North Karelia Project (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Thus, identifying persons who can significantly influence others and understanding such individuals’ involvement in promoting healthy behaviour will benefit the success of health interventions.\u003c/p\u003e \u003cp\u003eSocial network analysis (SNA) can quantify the social relationships that exist between individuals or agencies of interest, and at the same time, it can qualitatively describe or graphically present the structure of social relationships (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Thus, it can provide a quantitative and qualitative understanding of the social relationships among people and agencies by measuring the density and centrality of these relationships. Density refers to the number of links within a social network relative to all possible links, and it is a measurement of the closeness among network members. Centrality measures the interconnectedness among network members at the individual level (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Centrality measures how important a member is to the network. A member with a higher centrality indicates that the member plays a key role in the network (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The degree centrality measures the number of connections that a member has. The closeness centrality measures the shortest distance between two members. Higher closeness centrality indicates a close connection between two members. Betweenness centrality measures the mediating role of network members. It shows the shortest links between other members through the members of interest. A higher betweenness centrality results in a greater influence on the information or command flow within the network (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). These measurements provide an understanding of community social networks and network members' social connectedness (centrality). Such information is important for planning, implementing, monitoring and evaluating behaviour change interventions and programmes (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSustainable development goals (SDG) three and eight are directly related to health and the workforce (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). A healthy workforce is a key requirement for economic development and is the baseline for achieving most SGD targets. Furthermore, the workforce represents a vast majority of the population. In Sri Lanka, workforce participation was 52.3% in 2019 (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). More than half (57.9%) of the working population is formally employed, and 14.9% is employed in the public sector. According to the 2016 census, there are approximately 1.1\u0026nbsp;million employees in the public and semi-government sectors (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Nearly half of the public and semi-governmental sector workers are office-based clerical workers who are sedentary at work. This makes them vulnerable to non-communicable diseases (NCD), and a higher prevalence of NCD has been noted in the Sri Lankan workforce (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Furthermore, they are less accessible to health services outside office hours, as most preventive health services are limited to office hours.\u003c/p\u003e \u003cp\u003eWorkplace-based interventions effectively reduce NCD risk factors (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), as a homogenous group of people with similar risk factors are gathered in one place and tend to spend more than one-third of their day in offices. It is well documented that social ties and network characteristics can influence the effectiveness of behaviour change interventions. However, SNA and the effects of social relationships on health-related behaviours have not been adequately assessed in the local and regional context. The studies on the use of SNA data for understanding dietary behaviours and designing health interventions are minimal, even in global literature. Therefore, this study aimed to assess social relationships (as per network characteristics) and their associations with selected dietary behaviours and dietary intake among office workers in southern Sri Lanka. The current study will fill the research gap concerning the effects of social relationships on dietary behaviour and intake in the country and pave the way for further studies in this area. On the other hand, these research findings will enrich the global literature with evidence from a developing country in Asia.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eStudy setting\u003c/p\u003e\u003cp\u003eThis study was conducted in selected government offices in Galle District, Southern Sri Lanka. There are 78 government offices in the district. Five offices with more than 20–40 sedentary workers were purposefully selected to represent the district. Workers performing office-based clerical and administrative work were categorized as sedentary. Being at the office during the total working time was considered a supporting characteristic for assessing social relationships.\u003c/p\u003e\u003cp\u003eStudy participants and sampling procedure\u003c/p\u003e\u003cp\u003eDevelopment officers (DO), management assistants (MA), and administrative and management officers were considered sedentary workers and were recruited for the study. Workers who engaged in physical exertion during their duty hours by the nature of their work were excluded.\u003c/p\u003e\u003cp\u003eAn exhaustive list of government offices with the respective numbers of sedentary workers was prepared, and offices with 20–40 workers were shortlisted (n = 26). Five divisional secretariat offices were purposively selected from the shortlisted offices to ensure representation of all geographical areas of the district. They were Akmeemana (n = 23), Benthota (n = 31), Elpitiya (n = 29), Niyagama (n = 33) and Thawalama (n = 23).\u003c/p\u003e\u003cp\u003eStudy instruments and data collection\u003c/p\u003e\u003cp\u003eData on socio-demographic characteristics, health and work-related factors, and dietary practices were collected via a pretested, self-administered (survey) questionnaire (Supplementary file I). The participants were informed in advance to produce any previous clinical records (investigation reports, clinic records, etc.) at the time of data collection to verify health-related data. The weight and height of the participants were measured by trained data collectors adhering to the standard procedures described in the European Health Examination Survey (EHES) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), and body mass index (BMI) was calculated.\u003c/p\u003e\u003cp\u003eA trained medical officer obtained the dietary intake data for a typical office day via 24-hour dietary recall, which was supplemented by a picture guide to determine portion sizes. A computer software prepared specifically for the study was used to calculate the number of servings consumed from each food group based on the serving sizes described in the Food Based Dietary Guidelines (FBDG) for Sri Lankans − 2011(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHealthy dietary intake was defined as adherence to the number of servings recommended in the FBDG for Sri Lankans for more than three food groups, including cereal and cereal-based foods, fruits, and vegetables, with one or no unhealthy food per day.\u003c/p\u003e\u003cp\u003eA social network survey questionnaire was used to collect data on the participants' social relationships. Information/advice seeking was considered a social connection within the office, and the participants were asked the following questions.\u003c/p\u003e\u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eName five persons at the office from whom you seek information or advice on your official or personal matters.\u003c/p\u003e \u003cp\u003e\u003c/p\u003e\u003col style=\"list-style-type: lower-alpha;\"\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eArrange them from the most frequent to the least frequent contact.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003cp\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eName five persons at the office seeking information or advice from you.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003col style=\"list-style-type: lower-alpha;\"\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eArrange them from the most frequent to the least frequent contact.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003cp\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e\u003cp\u003eThe main questions (Nos. 1 and 2) identified the presence of social relations, and the two branching questions (1a and 2a) assessed their magnitude and weight.\u003c/p\u003e\u003cp\u003eA list of all workers in the respective offices was provided to answer the above questions, and participants were allowed to add any co-workers who were not included in the list.\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eSample characteristics were described under socio-demographic, health, and work-related factors. The independent variables are categorized as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eA directed and weighted network matrix was prepared for each office using the participants’ responses to the social network survey questions. Social Network Visualizer (SocNetV) software (version 3.1) was used to create the network graph and calculate network measures. Degree centrality and betweenness centrality were calculated for each individual (node) in the network, and density was calculated for the whole network.\u003c/p\u003e\u003cp\u003eNon-parametric tests (Mann-Whitney U test and Kruskal-Wallis test) were used to assess the statistical significance of the observed associations between network measures and other study variables at a probability level of 0.05. The analyses were performed using Statistical Package for Social Sciences (SPSS) software.\u003c/p\u003e\u003cp\u003eEthical and administrative clearance\u003c/p\u003e\u003cp\u003e This study adhered to the World Medical Association Declaration of Helsinki on ethical principles for medical research involving human subjects. Ethical approval for the study was obtained from the Ethics Review Committee, Faculty of Medicine, University of Ruhuna (Registration No. 2020/P/105). Administrative approval was obtained from all the relevant authorities (District Secretary, Galle District, and Regional Director of Health Services, Galle District). Informed written consent was obtained from all participants prior to data collection. Workers identified as having health issues were referred to the nearest healthcare facility with their consent.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 139 office workers participated in this study (response rate: 85.3%). The mean age of the participants was 39 (SD\u0026thinsp;=\u0026thinsp;8) years, and the ages ranged from 26 to 59 years. Half of the participants (50.0%) were in the 30\u0026ndash;39 years age group, and the vast majority (80.4%) were female. Most of the participants (93.5%) were educated up to the General Certificate of Education (GCE) (Advanced Level) or above. Nearly three-fourths of the participants (75.5%) belonged to the clerical and supportive workers category, and the remaining participants were from the managerial, professional, technical, and associate worker categories. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the socio-demographic characteristics of the participants.\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 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of the participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHighest educational qualification**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePassed GCE Ordinary Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePassed GCE Advanced Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLegally married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/Widowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of living children\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent post held\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManagerial posts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfessionals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnical and associate officers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClerical and supportive officers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTime taken to travel for work (in minutes)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;60 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60 minutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMethod of transport\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOn foot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic transport\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrivate vehicle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e*n\u0026thinsp;=\u0026thinsp;120, 19 missing/**n\u0026thinsp;=\u0026thinsp;138, 1 missing/***n\u0026thinsp;=\u0026thinsp;516, 2 missing\u003c/p\u003e \u003cp\u003eGCE \u0026ndash; General Certificate of Education\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNearly two-thirds of the participants (63.3%) consumed at least one snack daily, and a significant percentage (64.7%) of office workers had meals in groups. Meal skipping was common among office workers because of their workload and external or internal meetings. Almost all the participants consumed food prepared at home as their main meal (breakfast, lunch, and dinner). Among the 88 participants who consumed snacks, only seven (8.0%) reported having homemade snacks, while 60 (68.2%) of participants had snacks prepared elsewhere (office canteen or outside food stalls). However, 21 (23.8%) participants did not report the source of their snacks. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e describes the participants\u0026rsquo; dietary behaviours.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of selected dietary behaviours among the participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eNumber of snacks consumed per day*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHaving meals in groups\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMeal skipping\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne or more meals per week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003e*\u003c/b\u003en\u0026thinsp;=\u0026thinsp;88, 51 missing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe overall dietary intake of the office workers was not satisfactory, and only 5% of the participants met the FBDG recommendation for more than three food groups, including cereal and cereal-based foods, fruits, and vegetables, with one or no unhealthy food per day. However, most met the recommended number of daily servings for cereal-based products and \u0026ldquo;fish, meat, and pulses\u0026rdquo; food groups. Interestingly, fruit and vegetable intake was suboptimal, dairy food intake was minimal, and none of the participants consumed nuts or seeds. Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the dietary intake of office workers according to the food groups described in FBDG for Sri Lankans.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe dietary intake of office workers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFood group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNumber of servings consumed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of servings recommended in FBDG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber (%) having recommended minimum number of servings\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCereal based products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.0 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.7 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u0026ndash;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVegetables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.8 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFruits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFish, meat, pulses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDairy products\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNuts and seeds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnhealthy foods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.9 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRecommended to have sparingly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.9*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e*Having none or one serving of unhealthy foods per day\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong the participants. interpersonal relationships were noted both during and beyond office time. However, 41 (31.7%) workers claimed they did not have relationships with coworkers beyond office time. Interestingly, direct or in-person contact was the most common method of contact during office hours, whereas telephone calls were the most common method of contact beyond office hours. Emails, SMS, and social media were used somewhat in social relationships. The density of social networks in offices was low (Akmeemana \u0026ndash; 0.0434, Benthota \u0026ndash; 0.0459, Elpitiya \u0026ndash; 0.0490, Niyagama 0.0392), except for one office (Thawalama \u0026ndash; 0.1708) (Supplementary file II). This showed fewer connections between office workers. Similarly, the results revealed low in- and out-degree centralities among the participants, confirming low social relations within most offices. On the other hand, relatively high betweenness centrality also highlighted the low levels of social relations among participants. Notably, all centrality measures showed a skewed distribution. While out-degree centrality showed positive skewness, in-degree and betweenness centrality showed negatively skewed distributions. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e summarizes the measures of degree centrality and betweenness centrality.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary measures for centrality in social relationships among office workers\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=\"left\" 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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eNetwork measurement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-degree centrality (actual)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e9.0 (9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.0 (9.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-degree centrality (percentage)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2.4 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.8 (2.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOut-degree centrality (actual)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e13.3 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOut-degree centrality (percentage)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e3.5 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.7 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetweenness centrality (actual)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e91.3 (124.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.0 (115.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetweenness centrality (percentage)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e4.6 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9 (6.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHaving a tertiary education was significantly associated with higher in-degree centrality, whereas having a healthy diet was significantly associated with higher out-degree centrality. However, betweenness centrality was not associated with any of the variables assessed. Socio-demographic variables such as marital status, number of children, and worker type failed to show a statistically significant association with any centrality measure. Dietary behaviours, such as skipping meals and having snacks, were not associated with any centrality measures. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e5\u003c/span\u003e summarizes the statistical analysis results assessing the associations between centrality measures, sociodemographic variables, and dietary habits.\u003c/p\u003e\u003cdiv class=\"gridtable\"\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\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociations of centrality measures with the socio-demographic variables and dietary habits of the office workers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eIn-degree centrality\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eOut-degree centrality\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eBetweenness centrality\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHad tertiary education\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39.0\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\"\u003e \u003cp\u003eEver married\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.0\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\"\u003e \u003cp\u003eClerical worker\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.8\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\"\u003e \u003cp\u003eNumber of children\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo children\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne child\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37.8\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\"\u003e \u003cp\u003eTwo or more children\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.0\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\"\u003e \u003cp\u003eNumber of snacks per day\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.0\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\"\u003e \u003cp\u003eTwo or more\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.0\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\"\u003e \u003cp\u003eGroup eating\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.7\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\"\u003e \u003cp\u003eMeal skipping\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.3\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\"\u003e \u003cp\u003eHaving a healthy diet\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e118.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current study assessed social relationships (as per network characteristics) and their associations with selected dietary behaviours and dietary intake among office workers at five offices in the Galle district. The findings revealed that social relations are not strong among office workers (in terms of density and centrality measures), and direct contact and telephone conversations are common methods of contact during office hours and beyond office hours, respectively. Furthermore, this study highlighted the presence of undesirable dietary habits (meal skipping and group eating) and suboptimal dietary intake among office workers. A degree or higher education qualification was associated with higher in-degree centrality, whereas healthy eating was associated with higher out-degree centrality. None of the other variables tested showed associations with centrality measures. This discussion focuses mainly on the significance of the above findings with respect to the literature and local context, their implications, and recommendations for further research on social relationships, dietary behaviours, and intake.\u003c/p\u003e \u003cp\u003eNearly three-fourths of the participants (72.5%) were in the 30–49 age group. Therefore, the sample was composed of relatively young participants, which needs to be considered when interpreting the study findings. The majority (80.4%) of the study participants were female. Although the Sri Lankan workforce is male dominated, its composition and sex distribution can vary across different sectors (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Similar findings regarding sex distributions have been reported in a previous study conducted in the Colombo District (Swarnamali et al., 2017). Most workers (93.5%) were educated at the advanced GCE level or had completed tertiary education. Development officers and management assistants require a degree and GCE Advanced Level educational qualifications. Swarnamali et al. (2017) reported similar education levels among public sector workers in the Colombo District. The percentages of participants using public transport and walking to reach the workplace (50.4% and 5.0%, respectively) are consistent with data from the 2016 census of public sector workers, where 46.7% used public transport and 5.7% walked to reach the office (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). This indicates the representativeness of our study sample of office workers in a sedentary working environment in the local context. Interestingly, nearly 75% of the workers belonged to the clerical and supportive worker category, whereas the rest belonged to the manager, professional, and technical officer categories. We believe that this composition ensured the effective capturing of social relations because officers in the same category will have more personal relations among them. Personal relations are more influential on personal behaviours than official relations with different categories.\u003c/p\u003e \u003cp\u003eUnhealthy snacking was common among office workers in this study, with 63.3% consuming one or more snacks daily. Several studies have highlighted the increased snack consumption among office workers in Southeast Asia and globally (\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e–\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Consistent with similar studies (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), nearly 40% of the participants reported skipping meals. Nearly two-thirds (64.7%) of the participants reported eating in groups. Previous studies have highlighted group eating as a factor associated with high calorie intake (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) and unhealthy dietary intake (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), though only a few studies have focused on social relationships and group eating (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). However, we believe that group eating shows more significant social ties within groups, and further studies are needed to evaluate its influence on dietary intake.\u003c/p\u003e \u003cp\u003eThe current study reported suboptimal dietary intake with low fruit and vegetable intake and high unhealthy food intake. Swarnamali et al. (2017) reported low fruit and vegetable and high added sugar intake among Sri Lankan office workers. Low fruit and vegetable intake has also been highlighted among the general Sri Lankan population in the STEPs survey (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Furthermore, Swarnamali et al. (2017) reported high starchy food intake, whereas the current study reported only a marginally high intake. A marginally high consumption of carbohydrates among public sector workers was evident in another large-scale study conducted in Sri Lanka (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNetwork density was low in all offices, indicating weak social relationships among office workers. There were hardly any studies that assessed network density alone in office workers. Two studies have reported higher density among office workers and have highlighted that a greater network density is associated with greater worker performance (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e) and job satisfaction (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). A study among healthcare workers in Canada revealed low-density networks among healthcare workers seeking information. Furthermore, the same study highlighted clustering within organizational divisions (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). The reported low density may have resulted from multiple functional divisions within an office. However, a study of nurses revealed that a higher number of staff members resulted in a lower density (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). We believe the offices with reasonably high staff numbers and internal functional divisions included in the current study resulted in low-density values.\u003c/p\u003e \u003cp\u003eThe current study reported higher betweenness centrality than in- and out-degree centrality. This is explained by the low-density networks and functional divisions within the offices. Relations are limited to functional divisions, and most office workers appear as mediators within the shortest path connecting two workers.\u003c/p\u003e \u003cp\u003eHigher median centrality (in-degree, out-degree, and betweenness) values were associated with tertiary education among the office workers. However, only in-degree centrality was significantly associated with tertiary education. Multiple studies have reported a positive correlation between education level and degree centrality (\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e–\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Notably, females with higher educational levels had a higher degree of centrality (Ajrouch et al. 2005; Fang and Zhang 2014). Thus, the higher percentage of females in the current study would also explain the higher centrality in the tertiary education group.\u003c/p\u003e \u003cp\u003eThere is conflicting evidence regarding the association between the number of children and degree centrality measures. The number of children was not significantly associated with centrality measures in this study. In contrast, a study conducted in Israel showed that centrality measures could vary by gender and having children or parenting reduces centrality among females, whereas males have an inverse association (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). The same study also highlighted that job category can change the direction of such associations. Higher centrality has been reported for parenting males and females in higher job categories (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). A large-scale study conducted on workers in 11 countries concluded that having children could increase the degree of centrality in both men and women (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). The job category was also identified as an important determinant of degree centrality. This is explained by the fact that the higher the category is, the more opinions you will be asked for, and vice versa (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). However, this study failed to show an association between occupation and centrality measures. This finding must be interpreted cautiously because the low number of workers in categories other than clerical and supportive workers can distort the association.\u003c/p\u003e \u003cp\u003eSeveral studies showed associations between social relationships, dietary behaviour, and dietary intake. Most such studies have been conducted among adolescents, where peer influence is more prevalent regarding dietary intake and behaviour. A few systematic reviews have concluded that dietary intake and behaviour are associated with social relationships (\u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e–\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). However, none of these studies have assessed the associations between an individual’s social network characteristics and dietary intake and behaviour. The present study fills this void by assessing the associations between participants’ social network characteristics, such as centrality, and their dietary intake and behaviour. A higher out-degree centrality was associated with healthier dietary intake. This implies that workers who are reached by others have healthier dietary intake. However, no other network measurements showed associations with dietary intake or behaviours such as meal skipping and group eating. This should be interpreted with caution because office workers with a healthy dietary intake accounted for only 5% of the sample. Although the frequent consumption of snacks and other unhealthy behaviours were found to be associated with social networks in adolescents, the current study failed to establish such associations with network measurements. We believe that the age composition and the nature of relationships (mostly official and non-influential in personal decision-making) have contributed to these contrasting findings.\u003c/p\u003e \u003cp\u003eConsidering their geographical distribution, the offices were selected to represent the entire district, and workers involved only in office-based work were included in the study. Therefore, the study sample is reasonably representative of the office-based workers in the Galle District, ensuring the external validity of the study. Moreover, the current study focused on participants’ characteristics within networks and their associations with dietary intake and behaviour - a phenomenon which has not been widely studied in literature. Despite the above strengths, this study has several limitations. First, we observed that the network captured through relational questions was more focused on official relationships rather than personal or emotional relationships that can alter diet and dietary behaviour. Furthermore, we did not consider subgroups and clustering within the office in the data analysis, as it was outside the scope of the current study.\u003c/p\u003e "},{"header":"Conclusion and recommendations","content":"\u003cp\u003eIn conclusion, office workers had weak social relationships; direct contact and telephone calls were the main contact methods. Unhealthy dietary behaviours (snacking, group eating, and meal skipping) were common, and dietary intake was suboptimal, with low vegetable and fruit intake. Higher in-degree centrality was associated with the office workers' higher educational status, and higher out-degree centrality was associated with healthy eating.\u003c/p\u003e\u003cp\u003eWe recommend further studies on social relationships and their associations with dietary intake and behaviours in broader community settings, focusing more on personal and informal social relationships that can influence health behaviour and behaviour change. In addition, we believe that longitudinal studies on social relationships and dietary behaviour will firmly establish the associations identified in the current study. Further, we recommend including workers with higher out degree centrality and healthy dietary intake as changing agents in health promotion interventions in office settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Body Mass Index\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Confidence Interval\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDALY\u0026nbsp; \u0026nbsp;\u0026nbsp;Disability Adjusted Life Years\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDO\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Development Officer\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEHES\u0026nbsp; \u0026nbsp;European Health Examination Survey\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFBGD\u0026nbsp; \u0026nbsp;Food Based Dietary Guidelines\u003c/p\u003e\n\u003cp\u003eFBDG-SL \u0026nbsp; Food Based Dietary Guidelines for Sri Lankans\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGBD\u0026nbsp; \u0026nbsp; \u0026nbsp;Global Burden of Disease\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGCE\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;General Certificate of Education\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIQR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Inter Quartile Range\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Management Assistant\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNCD\u0026nbsp; \u0026nbsp; \u0026nbsp;Non-Communicable Disease \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Standard Deviation\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWHO\u0026nbsp; \u0026nbsp;\u0026nbsp;World Health Organization\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYLL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Years of Life Lost\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that\u0026nbsp;Ethical approval for the study was obtained from the Ethics Review Committee, Faculty of Medicine, University of Ruhuna (Registration No. 2020/P/105). Administrative approval was obtained from the District Secretariat Galle District and Regional Director of Health Services-Galle District. Informed written consent was obtained from all office workers before data collection. Workers identified with problems were referred to the nearest healthcare facility with consent.\u0026nbsp;\u0026nbsp;The study was conducted while adhering to the World Medical Association Declaration of Helsinki on ethical principles for medical research involving human subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the current study consent for publication is \u003cstrong\u003enot applicable\u003c/strong\u003e as no individual-level data with identification was included in the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the following link.\u003c/p\u003e\n\u003cp\u003ehttps://drive.google.com/drive/folders/1AnydiyNCPgHTf4MXty9E73_m_JTtSpCm?usp=sharing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;study was self-funded by the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJG planned the research project, data collection, statistical analysis and manuscript writing. CJW and MSDW provided technical guidance and supervised the research project. All authors read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors acknowledge the District Secretary-Galle District and the Chief Secretary-Sothern Province for granting administrative approval for the study and all Divisional Secretaries and Heads of local authorities supporting the project. Dr. Sithara Kulathunga, Dr. Sulekha Peellage and Dr. Isuri Sandunika are acknowledged for their contribution in data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCambridge University Press \u0026amp; Assessment. Cambridge English Dictionary and Thesaurus [Internet]. 2025 [cited 2025 Apr 7]. Available from: https://dictionary.cambridge.org/dictionary/\u003c/li\u003e\n\u003cli\u003eSakowski P, Marcinkiewicz A. 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Eat Behav. 2015 Aug 1;18:7\u0026ndash;15. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Social relations, Dietary intake, Dietary behaviour, Office workers, Social network analysis","lastPublishedDoi":"10.21203/rs.3.rs-6415036/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6415036/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOffice-based workers are sedentary and have a greater risk and prevalence of non-communicable diseases (NCD). Social relationships and influences are associated with dietary behaviour and intake and can be used to change them. The Current study was conducted to assess social relationships and their associations with selected dietary behaviours and intake among office workers in a Sri Lankan setting.\u003c/p\u003e \u003cp\u003eOffice-based workers from five offices representing an entire district in southern Sri Lanka were selected as the study sample. Socio-demographic and dietary behavioural data were collected via a self-administered questionnaire. The 24-hour dietary recall was used to assess dietary intake. Relational questions with an inductive list of office workers were used to capture social relationships. Social Network Visualizer (SocNetV) software (version 3.1) created a network graph and calculated network measures. Nonparametric tests were used to assess statistical significance.\u003c/p\u003e \u003cp\u003eThis study included 139 participants (response rate, 85.3%). Social relations were not strong among office workers (in terms of density and centrality measures), and direct contact (85.6%) and telephone conversations (84.2%) were common methods of contact during and beyond office hours, respectively. Meal skipping (39.6%) and group eating (64.7%) were common. Only 5% of the workers had a healthy dietary intake. Having a degree or higher education qualification was associated with higher in-degree centrality (p\u0026thinsp;=\u0026thinsp;0.02), and healthy eating was associated with higher out-degree centrality (p\u0026thinsp;=\u0026thinsp;0.02). None of the other dietary variables tested showed an association with centrality measures.\u003c/p\u003e \u003cp\u003eOffice workers have weak social relationships. Unhealthy dietary behaviours are common, and dietary intake is suboptimal. Higher in-degree and out-degree centrality were associated with tertiary education and healthy eating. We recommend further studies on social relationships and their associations with dietary intake and behaviours in broader communities, focusing on personal and informal social relationships.\u003c/p\u003e","manuscriptTitle":"Social relationships as determinants of dietary habits and intake among office-based workers: A social network analysis in southern Sri Lanka","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-16 12:10:29","doi":"10.21203/rs.3.rs-6415036/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-14T11:15:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-08T08:59:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-28T04:30:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"275772555330097169271362904185790038088","date":"2025-05-27T04:12:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-17T14:33:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"157163044862685785414883230137890423456","date":"2025-05-15T03:44:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"271564511490495302738899434934398994213","date":"2025-05-14T13:10:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-14T08:28:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-14T08:43:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-10T08:52:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-10T08:50:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-04-09T23:06:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"92213be2-e4d4-4b5b-bcd4-11608599206f","owner":[],"postedDate":"May 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T17:08:33+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-16 12:10:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6415036","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6415036","identity":"rs-6415036","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}