Prevalence and determinants of healthy and balanced diet among office workers in Southern Sri Lanka

doi:10.21203/rs.3.rs-4995506/v1

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Prevalence and determinants of healthy and balanced diet among office workers in Southern Sri Lanka

https://doi.org/10.21203/rs.3.rs-4995506/v1

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Background

An unhealthy diet is a key risk factor for non-communicable diseases (NCD), which account for a significant number of premature deaths and disability adjusted life years worldwide. Office workers are reported to have unhealthy and unbalanced diets, while being sedentary due to the nature of their work, placing them at a greater risk of NCD. This study aimed to determine dietary intake and associated factors among office workers in Southern Sri Lanka.

Methods

A cross-sectional study was conducted among 518 clerical workers in 20 offices in the Galle district. Socio-demographic, health, and work-related data with details on dietary practices were collected using a self-administered questionnaire. Twenty-four-hour dietary recall was used to assess dietary intake, which was converted into the number of servings of each food group. Healthy dietary intake was defined as ‘adherence to the numbers of servings recommended in Food Based Dietary Guidelines for Sri Lankan for more than three food groups including cereal and cereal-based foods, fruits, and vegetables, with the consumption of one or no unhealthy food per day’.

Results

Only 4.6% (n = 24) of the participants consumed a healthy diet, while a considerable proportion had the recommended intake of cereal-based foods, vegetables and fish, meat and pulses (65.3%, 65.8% and 50.8%, respectively). Fruit, dairy product, nut and seed intake was low among the participants. Meal skipping and group eating were significantly associated with an overall unhealthy diet. Stratified analysis showed sex as an effect modification for the association between group eating and unhealthy diet. In multivariate analysis none of the factors showed significant association with healthy dietary intake.

Conclusions

Dietary intake was suboptimal among Sri Lankan office workers, and selected eating behaviours are associated with an unhealthy dietary intake. This study recommends introducing health-promoting interventions for office workers to control dietary risk factors.

Healthy eating

Dietary intake

Eating behaviours

Dietary risk factors

Office workers

Stroke and ischaemic heart disease (IHD), the most common and serious complications of non-communicable disease (NCD), account for 17.4% of the total years of life lost (YLL) and 12.7% of the total disability-adjusted life years (DALY) globally (1). Alarmingly, both mortality and morbidity due to NCD mostly occur in the 30–70-year age group and in low- and middle-income countries (2). Similarly, NCD has been the leading cause of death in Sri Lanka in recent years, accounting for more than three-fourths of deaths (3), and contributed to most of the DALYs in the country in 2019 (4)

The key risk factors for NCDs such as cardiovascular disease, diabetes, and cancer, are well established and include tobacco use, harmful alcohol use, unhealthy diet, and physical inactivity (5). WHO stepwise approach to NCD risk factor surveillance conducted in Sri Lanka in 2015 revealed a higher prevalence of unhealthy diet and physical inactivity among both males and females (6).

The Global Burden of Diseases (GBD) study noted that unhealthy or suboptimal dietary practices accounted for 11 million deaths and 255 million DALYs in 2017 (7). Several studies have identified the casual and protective effects of diet on cardio-metabolic disorders (8).

In Sri Lanka, 52.3% of the total population participates in the workforce, 57.6% of which consists of professionals, technical and associate workers, and clerical categories who perform office-based duties except in the Departments of Health and Education (Department of Census & Statistics, 2016). Thus, a significant proportion of workers are sedentary due to their nature of work, and their diet can play a major role in the risk of developing NCDs in the workforce.

The Food-Based Dietary Guidelines (FBDG) generally recommend having a varied and balanced diet while increasing fruit and vegetable intake and reducing fat, sugar, and salt intake (9). Similarly, the FBDG for Sri Lankans (FBDG-SL) also recommend having a variety of foods in adequate amounts (10). Thus, the level of adherence to FBDG would be an appropriate measure to assess diet quality among office workers.

As highlighted by both systematic reviews and observational studies, dietary risk factors are found to be more common among office workers, and their dietary intake, according to global and local recommendations, is suboptimal (11). The dietary intake of office workers has not been well studied globally or locally. Previous studies have focused mainly on the intake of selected food groups, such as fruits, vegetables and salt, rather than assessing overall intake of a healthy and a balanced diet (11). Two studies conducted in Sri Lanka in 2015 and 2017 reported increased intake of carbohydrates and added sugar and decreased intake of fruits and vegetables (12, 13).

The Academy of Nutrition and Dietetics of America has proposed a socio-ecological model for factors affecting diet and dietary behaviour. It describes the factors affecting diet under broad categories, such as individual factors, environmental settings, sectors of influence, and social and cultural norms and values (14). Individual factors such as age, sex, and ethnicity were identified as determinants of dietary intake and dietary behaviour (14). Understandably, nutritional knowledge was found to be associated with better dietary behaviours in several studies in both high- and low-income populations (15, 16) and work-related factors such as busy schedules and time constraints were associated with unhealthy dietary practices among the working population in USA (17, 18). However, there is a notable lack of studies assessing the factors associated with dietary intake in developing countries, particularly among high-risk populations such as office workers.

As an unhealthy and unbalanced diet is a well-established risk factor for developing future NCDs and the office workers’ risk for NCD is high due to the sedentary nature of their work, it is important to study the prevalence and determinants of unhealthy and unbalanced diets among this population. Further, an in-depth understanding of unhealthy and unbalanced dietary intake among office workers is essential in planning and implementing interventions to improve diet quality and thus prevent future risks of NCD. On the other hand, socio-economic and cultural factors associated with unhealthy and unbalanced diets in developing countries are yet to be explored.

Therefore, this study aimed to assess the dietary intake and related practices among office workers in the Galle district, in Southern Sri Lanka, and to determine the factors associated with unhealthy and unbalanced diets. The study will indicate the magnitude of unhealthy and unbalanced dietary intake among office workers in the country while enhancing the existing international knowledge base with findings from the socioeconomic and cultural contexts of a developing country in Southeast Asia. Further, the study will provide valuable insights into dietary intake assessment in local socio-cultural contexts. This study defines a healthy and balanced diet based on FBDG Sri Lanka. Therefore, it will contribute to global evidence on adherence to FBDG in different regions. Further, this study will highlight factors affecting dietary intake, especially in developing countries in the Southeast Asian region bridging the global knowledge gap for factors associated with dietary intake in different socio-economical contexts.

On the other hand, the current study will provide directions on specific groups and factors to be targeted in interventions aiming at changing dietary behaviours among office workers and will enrich and shape further interventions aiming at a healthy and balanced diet for office workers. Ultimately, the study findings will be useful to keep the workforce healthy and to reduce direct and indirect healthcare costs in both local and global contexts.

Study design and setting

The study was a cross-sectional survey conducted in twenty government offices representing 19 Divisional Secretariat areas (a middle-level administrative division) in Galle District, Southern Sri Lanka. The selected offices included Divisional Secretariat offices and local authority offices that carry out administrative functions as per the directions given by central and local governments. The main office functions were clerical tasks and internal management work, performed by development officers (DO), management assistants (MA), and administrative and management officers.

Study population

Development officers (DO), management assistants (MA), and administrative and management officers were selected for the study. Workers who engaged in physical exertion during their duty and on special dietary plans were excluded from the study.

Sample size and sampling

The sample size was calculated using the formula suggested by Lwanga and Lameshow (1991) to estimate a population proportion. The prevalence of healthy dietary intake was assumed to be 0.3, as reported by the 2016 STEPS Survey (6). An alpha error of 5% and a beta error of 20% were allowed in the sample size calculation. As cluster sampling was performed, a design effect of 1.58 was also incorporated in calculating the sample size.

A multistage, mixed sampling method was used to obtain the desired sample size. Twenty offices were selected purposively at the first stage to include offices with 30–40 clerical-type workers in each office. From each office, a cluster of 30 workers were selected randomly from the employees’ name list using a random number generator and were invited to participate in the study.

Study instruments and data collection

Data on socio-demographic characteristics, health and work-related factors and dietary practices were collected using a pretested, self-administered (survey) questionnaire. Health-related data were verified with available clinical records. The weight and height of the participants were measured according to standard procedures described in the European Health Examination Survey (EHES) (19), and body mass index (BMI) was calculated.

The dietary intake of a typical office day was obtained by a trained medical officer using 24-hour dietary recall, which was supplemented by a picture guide to determine portion sizes. Computer software was used to calculate the number of servings described in the FBDG for Sri Lankans in 2011.

Healthy dietary intake was defined as ‘adherence to the number of servings recommended in 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’.

Statistical analysis

Sample characteristics were described under socio-demographic, health, and work-related factors. Dietary practices and intake were also described using descriptive statistics, and generalization of measures to the population was done with measures of dispersion (95% CI, SD, and IQR). Dietary intake was categorized as overall healthy or unhealthy intake based on FBDG for Sri Lankans. The chi-square test was used to assess the statistical significance of the observed associations between variables at a probability level of 0.05.

Multivariate analysis was conducted using multiple logistic regression to detect determinants of overall healthy dietary intake. The forward selection method was used to select variables for the model, and p values for entry and exit were kept at 0.05 and 0.1, respectively.

Ethical and administrative clearance

The study was conducted adhering 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 relevant authorities (District Secretariat Galle District, Provincial Ministry of Local Government, Regional Director of Health Services Galle District). Informed written consent was obtained from all participants before data collection. Workers identified with health issues were referred to the nearest healthcare facility with their consent.

Five hundred and eighteen office workers from 20 offices participated in the study (response rate 84.9%). The median age of the participants was 39.5 (IQR = 8) years, and the ages ranged from 23 to 59 years. The majority were females (81.9%), and approximately 95% were educated up to the General Certificate of Education (GCE) Advanced Level or above. Seventy-one per cent of the participants were clerical and supportive officers, while 15.2% were managers and professionals (Table 1).

Table 1

Socio-demographic and work-related characteristics of the participants (N = 518)
Characteristics	Number	Frequency (%)
Age
< 30 years	49	9.5
30–39 years	286	51.7
40–49 years	139	26.8
≥ 50 years	62	12.0
Sex
Female	424	81.9
Male	94	18.1
Highest educational qualification
Grade 6 to 11	3	0.6
Passed GCE Advanced Level	207	40.0
Tertiary education	307	59.4
Marital status
Unmarried	74	14.3
Living together	3	0.6
Legally married	436	84.2
Divorced/Widowed	5	0.9
Number of living children *
0	51	11.5
1	125	28.2
2	193	43.5
3 or more	75	16.8
Current post held
Managerial posts	64	12.4
Professionals	14	2.7
Technical and associate officers	72	13.9
Clerical and supportive officers	368	71.0
Time taken to travel for work (in minutes) **
< 30 minutes	288	56.1
30–60 minutes	170	33.1
> 60 minutes	55	10.8
Method of transport***
On foot	28	5.4
Public transport	245	47.5
Private vehicle	243	47.1
n = 444/n = 513, 5 missing / **n = 516, 2 missing GCE – General Certificate of Education

Health status and dietary practices of the office workers

The mean BMI of the sample was 24.2 (SD = 3.9) kgm^− 2, and 56.9% of the participants had a normal BMI according to the cut-off values recommended for Asian populations. However, more than one-third of the participants were overweight or obese (31.1% and 6.9%, respectively). Only 11.5% of the participants had a personal history of NCD (diabetes 3.7% and hypertension 2.9%), while 64.8% of participants had a family history of NCD in a first-degree relative.

Snacking was common among office workers, and almost all participants had snacks as a part of their routine office day diet. Approximately 60% reported having more than one snack per day. Group eating and meal skipping were also prevalent among the participants (65.3% and 32.3%, respectively). Table 2 summarises the health-related characteristics and dietary practices of the participants.

Table 2

Health-related characteristics and dietary practices of the office workers (N = 518)
Characteristics	Number	Frequency (%)
BMI category
Low	26	5.0
Normal	295	56.9
Overweight	161	31.1
Obese	36	6.9
Having a personal history of NCD*	59	11.5
Having a family history of NCD**	333	64.8
Number of snacks consumed per day
0	1	0.1
1	209	40.3
2	249	48.1
3 or more	60	11.5
Having meals in groups***
No	164	31.7
Yes	338	65.3
Meal skipping
None	351	67.8
One or more meals per week	167	32.3
n = 511, 7 missing / n = 514, 4 missing / **n = 502, 16 missing

Dietary intake of the office workers

When considering the intake of different food groups, the mean and median number of servings consumed were within the recommended range for cereal-based foods and vegetables (Table 3), and nearly two-thirds of the participants had recommended numbers of servings of these two food groups (65.3% and 65.8%, respectively). However, only half of the participants (50.8%) reached the recommended number of servings of fish, meat, and pulses, although the mean and median intakes were higher than the recommended range. The consumption of fruits, dairy products, nuts and seeds was low, with the mean and median number of servings consumed falling far below the recommended number of servings. The consumption of unhealthy foods was greater among participants with a mean/median of two, and only 36.7% consumed one or no unhealthy foods. Overall, only 4.6% of the participants (n = 24) met with the definition of a healthy diet.

Table 3

The numbers of servings of different food groups consumed by the participants (N = 518)
Food group	Number of servings consumed		Number of servings recommended in FBDG	Number (%) having recommended minimum number of servings
Food group	Mean (SD)	Median (IQR)	Number of servings recommended in FBDG	Number (%) having recommended minimum number of servings
Cereal based products	6.1 (2.1)	5.7 (3.3)	6–7	338 (65.3)
Vegetables	2.8 (1.5)	2.5 (1.8)	3–5	341 (65.8)
Fruits	0.6 (1.0)	0 (1.0)	2–3	57 (11.0)
Fish, meat, pulses	3.6 (2.2)	3.3 (2.2)	1–2	263 (50.8)
Dairy products	0.7 (0.8)	0.5 (1.0)	3–4	241 (46.5)
Nuts and seeds	0.01 (0.1)	0 (0)	2–4	32 (6.2)
Unhealthy foods	2.0 (1.3)	2 (2.0)	Recommended to have sparingly	190 (36.7)*
*Having none or one serving of unhealthy foods per day

Most participants (n = 407, 78.6%) consumed food from 3–4 food groups per day. Cereal-based foods, vegetables and fish, meat and pulses were the most consumed food groups.

Factors associated with healthy dietary intake

In univariate analysis, group eating and skipping meals were significantly associated with an unhealthy dietary intake (Table 4). None of the socio-demographic or work-related factors were associated with an unhealthy dietary intake. After including sex, education level, BMI, history of NCD, meal skipping, and group eating as predictor variables, a multivariate analysis was conducted. None of the variables included in the model showed a statistically significant association with healthy dietary intake.

Table 4

Factors associated with healthy dietary intake among office workers
Characteristic	Overall healthiness of the diet		Total No (%)	Odds Ratio	p value
Characteristic	Healthy No (%)	Not healthy No (%)	Total No (%)	Odds Ratio	p value
Age 40 years and above	15 (4.5)	320 (95.5)	335 (100.0)	0.9	0.82
Age less than 40 years*	9 (4.9)	174 (95.1)	183 (100.0)
Male	1 (1.1)	93 (98.9)	94(100.0)	0.2	0.07
Female*	23 (5.4)	401 (94.6)	424(100.0)
Had tertiary education	17 (5.5)	290 (94.5)	307(100.0)	1.7	0.24
No tertiary education*	7 (3.3)	204 (96.7)	211(100.0)
Married	22 (5.0)	414 (95.0)	436(100.0)	2.1	0.30
Unmarried/divorced/widowed*	2 (2.4)	80 (97.6)	82(100.0)
No children	7 (5.6)	118 (94.4)	125(100.0)	2.2	0.63
1 or 2 children	15 (4.7)	303 (95.3)	318(100.0)	1.8
More than 2 children*	2 (2.7)	73 (97.3)	75(100.0)
Clerical workers	19 (5.2)	349 (94.8)	368(100.0)	1.6	0.37
Other workers*	5 (3.3)	145 (96.7)	150(100.0)
Less than 30 min travel duration	16 (5.6)	272 (94.4)	288(100.0)	1.6	0.57
30 min-1 hour travel duration	6 (3.5)	164 (96.5)	170(100.0)	1.0
More than 1 hour travel duration*	2 (3.6)	53 (96.4)	55(100.0)
Travel on foot	0 (0.0)	28 (100)	28(100.0)	0.0	0.21
Travel by public transport	9 (3.7)	236 (96.3)	245(100.0)	0.6
Travel by private vehicle*	15 (6.2)	228 (93.8)	243(100.0)
Overweight or obese	12 (6.1)	185 (93.9)	197(100.0)	1.7	0.22
Low or normal BMI*	12 (3.7)	309 (96.3)	321(100.0)
Having a history of NCD	4 (6.8)	55 (93.2)	59(100.0)	1.8	0.32
No history of NCD*	18 (4.0)	434 (96.0)	452(100.0)
Having family history of NCD	12 (3.6)	321 (96.4)	333(100.0)	0.5	0.12
No family history of NCD*	12 (6.6)	169 (93.4)	181(100.0)
Having meals in group	8 (2.4)	330 (97.6)	338(100.0)	0.3	0.01
Having meals alone*	12 (7.3)	152 (92.7)	164(100.0)
Meal skipping	22 (4.3)	490 (95.7)	512(100.0)	0.1	0.00
No meal skipping*	2 (33.3)	4 (66.7)	6(100.0)
*reference category

Stratified analysis was conducted to assess the association of unhealthy dietary intake with meal skipping and having meals in groups within different categories of sex, education level, BMI and history of NCD. A significant difference between the odds ratios of group eating and unhealthy dietary intake was noted when stratified as males and females (p value for test of homogeneity of odds ratio = 0.036). However, stratified analysis did not reveal any other confounders or effect modifiers.

This study focused on dietary practices, healthy dietary intake, and associated factors among office workers in Sri Lanka. Most of the study participants (81.9%) were females. Although most of the workers in Sri Lanka are males, composition or sex distribution may vary in different sectors (20). Most workers (94.8%) were educated up to the GCE Advanced Level or had completed tertiary education. Posts of development officers and management assistants require a degree and GCE Advanced Level educational qualifications, respectively. The findings of the current study concerning sex distribution and education level are consistent with those of a similar study conducted in the Colombo district (12). Similarly, the percentages of participants using public transport and walking to reach the workplace are consistent with the data from the census of public sector workers in 2016, where 46.7% used public transport, and 5.7% percentage walked to reach the office (20).

The reported mean BMIs were 24.2 kgm^− 2, and 56.9% of the participants had a normal BMI, while 31.9% and 6.1% were overweight and obese, respectively (Table 2). A similar study conducted among office workers in the Colombo district reported a mean BMI of 24.11 kgm^− 2 (12). A comparable mean BMI (23.8 ± 3.6 kgm^− 2) was reported in a study among office workers in South India, which could possibly be due to similarities in their socio-cultural environment, dietary patterns and economic statuses with those of Sri Lanka (21). In contrast, a study conducted among Nepali industrial workers has reported a lower percentage with a normal BMI and higher percentages with overweight and obesity (46.8%, 35.8% and 11.1%, respectively) (22) However, a study of university workers in Saudi Arabia reported a higher mean BMI of 28.3 kgm^− 2, with 35.9% of participants having a normal BMI and 31.0% being overweight and 30.7% being obese (23). Many studies conducted in Southeast Asian countries have failed to report mean BMI values, hence, comparison should be attempted with caution as mean BMI values tend to change with the social, cultural and economic context.

The prevalence of NCD remained lower at 11.5% in the current study compared to labour force data (17%) (24). This can be explained by the relatively younger population in the present study, with ages ranging from 23 to 59 years {median = 39.5 years and interquartile range (IQR) = 8)}. In contrast, the labour force data included people over 60 as well. However, the reported values for the prevalence of diabetes and hypertension were lower in this study than in the study conducted in 2017 by Swarnamali et al., involving government office workers in the Colombo district of Sri Lanka. Furthermore, several studies conducted in India, Nepal and Thailand have reported a higher prevalence of chronic NCD among working populations (21, 22, 25). In contrast, a low prevalence of diabetes and hypertension has been reported in a study conducted among state workers in Ethiopia (26). The current study considered only patients with a confirmed diagnosis of chronic NCDs, possibly overlooking the undetected cases. This might have contributed to the low prevalence of chronic NCDs among the study sample.

Consistent with Swarnamali et al. (2017), the current study reports an almost similar mean number of servings consumed from various food groups, except cereal-based and unhealthy foods. However, the method used to calculate servings was not specified in the former study, making comparisons difficult. In contrast to the higher consumption of cereal-based or carbohydrate-containing food in the former study (15.4 servings), the current study reports only a marginally high level of consumption of cereal-based foods. Another large-scale study reported a marginally high consumption of carbohydrates among public-sector workers (13).

Of all food groups, cereal-based food (the main contributor to dietary carbohydrates) was the most consumed food group. Fish, meat, pulses and vegetables consumption was within the range recommended in FBDG-SL. In contrast, fruits, dairy products, nuts and seeds consumption was far below the recommended level.

Comparable studies assessing dietary intake among office workers at the regional level are lacking in the published literature. However, in a study conducted in Vietnam, a marginally low carbohydrate intake among young female workers was highlighted (27). The few existing studies support the low fruit and vegetable intake among office workers. A study among Saudi university employees also highlighted a lower consumption of vegetables and fruits, with only 14% of the participants consumed five or more servings of fruits and vegetables (23). A lower proportion of workers meeting the recommended fruit and vegetable consumption requirements has also been reported in studies in both developing and developed countries (28).

A higher education level has been identified as an important factor associated with healthy dietary intake in several studies (14, 15, 18, 29, 30). However, a secondary analysis of a large cohort of French women reported an inverse association between a healthy diet and university education compared to an education below a diploma (31). The current study failed to show any association between education level and healthy dietary intake. Similarly, socio-economic status was not associated with healthy dietary intake, as identified in many previous studies (29, 31). We believe that the relative homogeneity of the sample concerning education level and socio-economic status may have contributed to the observed lack of association between these variables and healthy dietary intake. This similarity in the contextual factors will make it easier to plan and implement interventions to improve the dietary intake among the office worker population.

The existing evidence on association of age with healthy dietary intake has been inconclusive. Some studies have shown that older age is associated with a healthy dietary intake (31, 32), whereas others have reported the opposite (29, 30). The current study also failed to establish a statistically significant association between age and healthy dietary intake.

Healthy dietary intake was associated with female sex. However, it was not statistically significant (p value = 0.07). Sex or gender has been identified as a factor associated with food choices and healthy dietary intake. A review of nutritional surveys and studies in several Western countries confirms the link between female sex and healthy dietary intake. On the other hand, the same review pointed out few studies that showed no significant association between sex and dietary intake (33). Another study among Mexican Americans showed that young males are more prone for unhealthy eating (34). We believe that low male participation might have resulted in the association which is not statistically significant.

Anthropometric measurements such as weight, BMI, waist circumference and body composition are proven to be associated with dietary intake. A whole grain-based diet with vegetables, fruits, seafood and dairy products was associated with better anthropometric measurements (35). Several studies have highlighted the association of high BMI, overweight and obesity with diets high in carbohydrates, fat and sugar and low in vegetables and fruits (36–38). However, the current study did not show an association between dietary intake and BMI. Similar findings have been reported in a study in Malaysia (39) and among Mexican Americans (34). The former study claims that the homogeneity of the study sample and the study's cross-sectional nature could have led to these findings (39). Therefore, we also believe that the homogeneity of the sample and the study design might have contributed to the current study's findings.

Although the association between unhealthy dietary intake and NCD has been well documented in recent years (5, 7), the current study failed to show such an association. The reported prevalence of NCDs was lower in the study sample than in the labour force data (24). Therefore, we assume that NCD status and undetected cases in the sample might have been underreported.

Previous studies have highlighted that eating together can increase the amount of food consumed and total energy intake (40, 41). Furthermore, meal skipping and a busy work schedule were identified as factors associated with unhealthy dietary intake and poor diet quality through studies conducted in other settings (17, 18, 42, 43). The current study revealed an association of unhealthy diet with group eating and meal skipping during the univariate analysis, however, these variables did not show an association with dietary intake in the multivariate analysis.

Group eating and unhealthy dietary intake were associated differently among males and females. Thus, indicates sex can act as an effect modificatory in the association between group eating and unhealthy dietary intake. Although no previous research evidence was found on the effect modification of sex or gender for association between group eating and unhealthy dietary intake, several studies highlighted the effect of sex or gender in different associations. A study conducted in Brazil showed an association between high salt intake and hypertension where the association was greater in women (44). The association of healthy eating index and hypertension in United States was shown to be inverse Lenier in females while being U-shaped in males (45). A significant interaction was noted between diet quality and gender resulting in changes in BMI among Australian adults (46). Therefore. Sex or gender is considered as an effect modifier for different associations with dietary intake. Further, a network analysis of factors associated with nutrition sex was identified to have a central role in interaction (47). In the current study, the interaction term was not significant in the multivariate analysis and the interpretation must be done cautiously as the male participation for the study was low.

The study was conducted to cover a whole administrative district, and the sample was representative of the office workers. Thus, the study findings can be generalized to all clerical-type office workers. The 24-hour dietary recall was used for dietary assessment, and it was supplemented with a picture guide and computer software to calculate serving sizes. Therefore, the dietary assessment was valid and reliable. However, the relative homogeneity of sample hinders the generalization of results to a broader population. In addition, cross-sectional design also fails to establish the temporality of associations.

In conclusion, dietary intake was suboptimal among office workers. Though cereal-based food and vegetable intake met the recommended serving number, the consumption of fruits, and dairy products was low. Dietary practices like group eating and meal skipping were associated with unhealthy dietary intake in univariate analysis but not confirmed by the multivariate analysis.

The current study recommends nutrition education and health promotional interventions to promote healthy dietary intake. We recommend further studies to assess the effect of practices such as group eating and meal skipping on healthy dietary intake in the.

BMI Body Mass Index

CI Confident 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

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 all relevant authorities (District Secretariat Galle District, Provincial Ministry of Local Government, 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 nearest healthcare facility with consent. 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/file/d/19FZtEtz0MusfCzwuhcF0IHCyR7ebgcmP/view?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 did the planning 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 for supporting the project. Dr. Rajith Hathamuna is acknowledged for technical support for computer application creation and operationalization. Dr. Sithara Kulathunga, Dr. Sulekha Peellage and Dr. Isuri Sandunika are acknowledged for their contribution in data collection.

World Health Organization. Global health estimates: Leading causes of DALYs and Deaths. 2023 [cited 2023 Sep 25]. THE GLOBAL HEALTH OBSERVATORY. https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/global-health-estimates-leading-causes-of-dalys
World Health Organization. Global action plan for the prevention and control of noncommunicable diseases 2013–2020 [Internet]. World Health Organization. 2013 [cited 2022 Jan 31]. https://apps.who.int/iris/handle/10665/94384
World Health Organization. Noncommunicable Diseases (NCD) Country Profiles, 2018 [Internet]. 2018. https://www.who.int/nmh/countries/lka_en.pdf?ua=1
Institute for Health Metrics and Evaluation. Sri Lanka Institute for Health Metrics and Evaluation [Internet]. 2020 [cited 2022 Feb 7]. https://www.healthdata.org/sri-lanka
Freisling H, Viallon V, Lennon H, Bagnardi V, Ricci C, Butterworth AS et al. Lifestyle factors and risk of multimorbidity of cancer and cardiometabolic diseases: a multinational cohort study. BMC Med [Internet]. 2020 Jan 10 [cited 2022 Jul 17];18(1). /pmc/articles/PMC6953215/
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. https://www.who.int/ncds/surveillance/steps/STEPS-report-2015-Sri-Lanka.pdf
Afshin A, Sur PJ, Fay KA, Cornaby L, Ferrara G, Salama JS et al. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet [Internet]. 2019 May 11 [cited 2022 Feb 1];393(10184):1958. /pmc/articles/PMC6899507/
Micha R, Shulkin ML, Peñalvo JL, Khatibzadeh S, Singh GM, Rao M et al. Etiologic effects and optimal intakes of foods and nutrients for risk of cardiovascular diseases and diabetes: Systematic reviews and meta-analyses from the Nutrition and Chronic Diseases Expert Group (NutriCoDE). PLoS One [Internet]. 2017 Apr 1 [cited 2022 Feb 2];12(4). Available from: /pmc/articles/PMC5407851/.
de Ridder D, Kroese F, Evers C, Adriaanse M, Gillebaart M. Healthy diet: Health impact, prevalence, correlates, and interventions. Psychol Health. 2017;32(8):907–41.
Nutrition Division Ministry of Health, editor. Food Based Dietary guidelines for Sri Lankans. 2nd ed. Colombo: Nutrition Division Ministry of Health; 2011.
Sukumar GM, Joseph B. Non-Communicable Diseases and Mental Health Disorders in Indian Workplaces: Elephant in the Room or Future of Occupational Health Practice. Indian J Occup Environ Med [Internet]. 2021 Oct 1 [cited 2022 Jul 27];25(4):189. /pmc/articles/PMC8815653/
Swarnamali AKSH, Jayasinghe MVTN, Katulanda P, IDENTIFICATION OF RISK FACTORS FOR SELECTED NON COMMUNICABLE, DISEASES AMONG PUBLIC SECTOR OFFICE EMPLOYEES, SRI LANKA. Lijhls [Internet]. 2017;1(2):12–24. https://grdspublishing.org/index.php/life/article/view/26
Jayasinghe M, Ranaweera K. Nutrition Assessment of Several Sects in the Sri Lankan Community. 2015;2:1–2.
Freeland-Graves JH, Nitzke S. Position of the academy of nutrition and dietetics: total diet approach to healthy eating. J Acad Nutr Diet [Internet]. 2013 Feb [cited 2022 Jul 28];113(2):307–17. https://pubmed.ncbi.nlm.nih.gov/23351634/
Beydoun MA, Wang Y. Do nutrition knowledge and beliefs modify the association of socio-economic factors and diet quality among US adults? Prev Med (Baltim) [Internet]. 2008 Feb [cited 2023 Jan 10];46(2):145–53. https://pubmed.ncbi.nlm.nih.gov/17698186/
Klohe-Lehman DM, Freeland-Graves J, Anderson ER, McDowell T, Clarke KK, Hanss-Nuss H et al. Nutrition knowledge is associated with greater weight loss in obese and overweight low-income mothers. J Am Diet Assoc [Internet]. 2006 Jan [cited 2023 Jan 10];106(1):65–75. https://pubmed.ncbi.nlm.nih.gov/16390668/
Bruhn CM. Consumer perceptions and concerns about food contaminants. Adv Exp Med Biol [Internet]. 1999 [cited 2022 Jul 29];459:1–7. https://link.springer.com/chapter/10.1007/978-1-4615-4853-9_1
Devine CM, Farrell TJ, Blake CE, Jastran M, Wethington E, Bisogni CA. Work Conditions and the Food Choice Coping Strategies of Employed Parents. J Nutr Educ Behav [Internet]. 2009 Sep [cited 2022 Jul 29];41(5):365. /pmc/articles/PMC2748817/
Tolonen H, editor. EHES Manual. Part B. Fieldwork procedures. 2nd ed. Helsinki, Finland: National Institute for Health and Welfare; 2016.
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]. https://www.statistics.gov.lk/Resource/en/PublicEmployment/census_reports/FinalReport2016.pdf
Holla R, Bhagawan D, Unnikrishnan B, Masanamuthu DN, Bhattacharya S, Kejriwal A et al. Risk Assessment for Diabetes Mellitus by Using Indian Diabetes Risk Score Among Office Workers of Health Institutions of South India. Curr Diabetes Rev [Internet]. 2022 Nov 26 [cited 2024 Jun 6];18(7). https://pubmed.ncbi.nlm.nih.gov/34823460/
Pyakurel P, Karki P, Lamsal M, Ghimire A, Pokharel PK. Cardiovascular risk factors among industrial workers: a cross–sectional study from eastern Nepal. J Occup Med Toxicol [Internet]. 2016 May 14 [cited 2024 Jun 6];11(1). /pmc/articles/PMC4867088/
Amin TT, Al Sultan AI, Mostafa OA, Darwish AA, Al-Naboli MR. Profile of non-communicable disease risk factors among employees at a Saudi university. Asian Pac J Cancer Prev [Internet]. 2014 [cited 2024 Jun 6];15(18):7897–907. https://pubmed.ncbi.nlm.nih.gov/25292084/
Department of Census, Statistics. labour force data [Internet]. Department of Census and Statistics, Battaramulla: Department of Census and Statistics. 2020. http://www.statistics.gov.lk/samplesurvey/LFS_Annual%20Report_2017.pdf
Aung TNN, Shirayama Y, Moolphate S, Lorga T, Jamnongprasatporn W, Yuasa M et al. Prevalence and Risk Factors for Hypertension among Myanmar Migrant Workers in Thailand. Int J Environ Res Public Health [Internet]. 2022 Mar 1 [cited 2024 Jun 7];19(6). /pmc/articles/PMC8955730/
Zegeye MY, Yosef T, Asres A. Prevalence of Diabetes and Associated Factors Among Government Employees of Mizan-Aman Town and Zonal Sector Office, Bench Sheko Zone, Southwest Ethiopia Region, 2022. Diabetes, Metabolic Syndrome and Obesity [Internet]. 2024 [cited 2024 Jun 7];17:725. /pmc/articles/PMC10870931/
Tran LM, Nguyen PH, Hoang NT, Truong DTT, Tran THT, Bui DN et al. Dietary intake and occupational status among female youths of Thai Nguyen, Vietnam. Ann N Y Acad Sci [Internet]. 2023 Sep 1 [cited 2024 Jun 7];1527(1):75–83. https://pubmed.ncbi.nlm.nih.gov/37501649/
Pem D, Jeewon R, Fruit, Intake V. Benefits and Progress of Nutrition Education Interventions- Narrative Review Article. Iran J Public Health [Internet]. 2015 Oct 1 [cited 2024 Aug 16];44(10):1309. /pmc/articles/PMC4644575/
dos Santos JEM, Crispim SP, Murphy J, de Camargo Cancela M. Health, lifestyle and sociodemographic characteristics are associated with Brazilian dietary patterns: Brazilian National Health Survey. PLoS One [Internet]. 2021 Feb 1 [cited 2024 Jun 14];16(2). /pmc/articles/PMC7886222/
Richards Adams IK, Figueroa W, Hatsu I, Odei JB, Sotos-Prieto M, Leson S et al. An Examination of Demographic and Psychosocial Factors, Barriers to Healthy Eating, and Diet Quality Among African American Adults. Nutrients [Internet]. 2019 Mar 1 [cited 2024 Jun 14];11(3). /pmc/articles/PMC6470798/
Affret A, Severi G, Dow C, Rey G, Delpierre C, Boutron-Ruault MC et al. Socio-economic factors associated with a healthy diet: results from the E3N study. Public Health Nutr [Internet]. 2017 Jun 1 [cited 2024 Jun 14];20(9):1574. /pmc/articles/PMC10261265/
Kanauchi M, Kanauchi K. The World Health Organization’s Healthy Diet Indicator and its associated factors: A cross-sectional study in central Kinki, Japan. Prev Med Rep [Internet]. 2018 Dec 1 [cited 2024 Jun 14];12:198. /pmc/articles/PMC6199773/
Grzymisławska M, Puch EA, Zawada A, Grzymisławski M. Do nutritional behaviors depend on biological sex and cultural gender? Adv Clin Exp Med [Internet]. 2020 [cited 2024 Aug 22];29(1):165–72. https://pubmed.ncbi.nlm.nih.gov/32017478/
Reininger B, Lee M, Jennings R, Evans A, Vidoni M. Healthy eating patterns associated with acculturation, sex and BMI among Mexican Americans. Public Health Nutr [Internet]. 2017 May 1 [cited 2024 Aug 22];20(7):1267. /pmc/articles/PMC10261606/
Boushey C, Ard J, Bazzano L, Heymsfield S, Mayer-Davis E, Sabaté J et al. Dietary Patterns and Growth, Size, Body Composition, and/or Risk of Overweight or Obesity: A Systematic Review [Internet]. 2020 Jul 15 [cited 2024 Jun 18]; https://pubmed.ncbi.nlm.nih.gov/35129906/
Martinchik AN, Baturin AK, Kambarov AO. [Analysis of the association of diet energy from macronutrients and prevalence of overweight and obesity among the Russian population]. Vopr Pitan [Internet]. 2020 [cited 2024 Jun 18];89(3):40–53. https://pubmed.ncbi.nlm.nih.gov/32790257/
Lee YY, Muda WAMW. Dietary intakes and obesity of Malaysian adults. Nutr Res Pract [Internet]. 2019 Apr 1 [cited 2024 Jun 18];13(2):159–68. https://pubmed.ncbi.nlm.nih.gov/30984360/
Eng JY, Moy FM, Bulgiba A, Rampal S. Dose-Response Relationship between Western Diet and Being Overweight among Teachers in Malaysia. Nutrients [Internet]. 2020 Oct 2 [cited 2024 Jun 18];12(10):1–15. https://pubmed.ncbi.nlm.nih.gov/33050612/
Arshad F, Nor IM, Ali RM, Hamzah F. Energy, protein, fat and carbohydrate intakes of underweight, normal weight and obese government office workers in an urban area. Asia Pac J Clin Nutr. 1996;5(2).
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. 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. https://pubmed.ncbi.nlm.nih.gov/16757007/
Herman CP, Roth DA, Polivy J. Effects of the presence of others on food intake: a normative interpretation. Psychol Bull [Internet]. 2003 Nov [cited 2022 Jul 23];129(6):873–86. https://pubmed.ncbi.nlm.nih.gov/14599286/
Liu M, Liu C, Zhang Z, Zhou C, Li Q, He P et al. Quantity and variety of food groups consumption and the risk of diabetes in adults: A prospective cohort study. Clin Nutr [Internet]. 2021 Dec 1 [cited 2022 Jul 23];40(12):5710–7. https://pubmed.ncbi.nlm.nih.gov/34743048/
Mill JG, Baldo MP, Molina M del, Schmidt CB, Barreto MI, Chor SM. D, Sex-specific patterns in the association between salt intake and blood pressure: The ELSA‐Brasil study. The Journal of Clinical Hypertension [Internet]. 2019 Apr 1 [cited 2024 Aug 22];21(4):502. /pmc/articles/PMC8030395/
Weng J, Mao Y, Xie Q, Sun K, Kong X. Gender differences in the association between healthy eating index-2015 and hypertension in the US population: evidence from NHANES 1999–2018. BMC Public Health [Internet]. 2024 Dec 1 [cited 2024 Aug 22];24(1). /pmc/articles/PMC10829399/
Fenton S, Ashton LM, Lee DCW, Collins CE. Gender differences in diet quality and the association between diet quality and BMI: an analysis in young Australian adults who completed the Healthy Eating Quiz. J Hum Nutr Diet [Internet]. 2024 Aug 1 [cited 2024 Aug 22];37(4). https://pubmed.ncbi.nlm.nih.gov/38664922/
Hoang T, Lee J, Kim J. Network analysis of demographics, dietary intake, and comorbidity interactions. Nutrients [Internet]. 2021 Oct 1 [cited 2024 Aug 22];13(10). /pmc/articles/PMC8539503/

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Prevalence and determinants of healthy and balanced diet among office workers in Southern Sri Lanka

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Abstract

Background

Methods

Results

Conclusions

Background

Methods

Study design and setting

Study population

Sample size and sampling

Study instruments and data collection

Statistical analysis

Ethical and administrative clearance

Results

Health status and dietary practices of the office workers

Dietary intake of the office workers

Factors associated with healthy dietary intake

Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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