Cardiometabolic risk and its association with dietary diversity, activity patterns and the nutritional status of workers in tertiary educational institutions in Southwestern Nigeria

Introduction Waist-to-height ratio (WHtR) is increasingly being reported as a simple, but accurate measure of cardiometabolic risk, even better than BMI, WHR and even waist circumference. Therefore, the objective of this study was to determine the cardiometabolic risk using WHtR, and its association with dietary diversity, activity patterns and the nutritional status of workers in tertiary educational institutions in Southwestern Nigeria. Materials and Methods This was a descriptive cross-sectional study carried out among workers in 3 randomly selected tertiary educational institutions in Osun State, Nigeria who were adults (18 years and above). Only apparently healthy people were recruited for the study. Cardiometabolic risk was assessed using WHtR, and respondents were categorized into low risk (WHtR < 0.5) or high risk (WHtR ≥ 0.5). Bivariate and multivariate (logistic regression model) analyses were used to determine the signicant predictors of cardiometabolic risk. Level of signicance was set at p-value less than 0.05. Results The mean age of the respondents was 45.8 ± 10.4 years, with a male:female ratio of 1:1.1. The mean WHtR among the respondents was 0.53 ± 0.08, and 36.5% had low cardio-metabolic risk while 63.5% had high cardiometabolic risk. The prevalence of overweight and obesity were 44.0% and 25.8% respectively using the BMI categories. At bivariate level, there were statistically signicant associations between WHtR and age (p < 0.001), gender (p = 0.002), educational level (p = 0.046), marital status (p = 0.022), dietary diversity (p = 0.027) and activity patterns (p = 0.030). When these were entered into a binary logistic regression model, age (p = 0.028; CI = 1.003 to 1.060) and gender (p = 0.010; CI = 1.149 to 2.784) remained the only statistically signicant explanatory variables for cardiometabolic risk using WHtR. Conclusion The study found a relatively high prevalence of cardiometabolic risk, overweight and obesity among the respondents, with age and gender being the main predictors of cardio-metabolic risk using WHtR. Therefore, there is a need for early screening for cardiometabolic risk using WHtR, especially among the females.


Background Information
Cardiometabolic risk is a broad term comprising risk factors for cardiovascular diseases which include obesity, hypertension, diabetes or dyslipidemia. [1] Globally, cardiovascular diseases contributed signi cantly to about 17.6 million deaths in 2016, making it the foremost cause of mortality resulting from non-communicable diseases. [2] Evidence from American National Survey has revealed that approximately 10% of the youth population exhibits clustering of cardiometabolic risks. [3] Reports also showed that approximately 114 million Chinese adults had diabetes mellitus and 265 million had hypertension in 2010. Similarly, in Nigeria, the National non-communicable disease survey, conducted on a cross-sections of Nigerians, found that there is an increase in the burden of cardiovascular diseases across the six geo-political zones of the country. [4,5] WHtR is increasingly being reported as a simple, but accurate measure of cardiometabolic risk, even better than BMI, WHR and even waist circumference. [6][7][8][9] For several years, BMI has been traditionally used as a predictor for total obesity. Evidences abound that central obesity carries more health risks in comparison with total obesity assessed by BMI. Although BMI is correlated with total body fat tissue, it does not take body fat distribution into account. [8,9] More recently, waist circumference (WC), waist-tohip ratio (WHR) and WHtR have been used as proxies for central obesity. [8] Waist-to-height ratio is increasingly being reported as the best measure of central adiposity and of cardiometabolic risk. [6][7][8][9] Understanding the relationship of cardiometabolic risks with modi able habits and practices like diet and physical activity is important because it holds a great potential for the prevention and control of the cardiometabolic risks and diseases. There is accumulating evidence that physical exercise may help in improving health via different mechanisms including a decrease in the percentage body fat and improvement in many cardio-metabolic risk factor levels obtained during blood assessment. [10] A balanced diet has also been shown to reduce cardiovascular disease (CVD) risk factors. [11] It is important to determine these relationships in different contexts and among different populations.
Cardiometabolic risks might not be the same across different regions and population groups due to differences in socioeconomic characteristics, culture, ethnicity, geographical location and even occupations. Tertiary educational institution workers may differ from the general population in terms of socio-economic status and their activity patterns. In Nigeria, few studies have focused on assessment of cardiometabolic risk among apparently healthy population using WHtR, and fewer still among tertiary educational institution workers. Therefore, the study aimed to assess cardiometabolic risk and its association with dietary diversity, activity plans and nutritional status among tertiary educational institution workers in Nigeria; and this is necessary and critical to design appropriate cardiometabolic and nutritional intervention programmes for this group.

Materials And Methods
The study was carried out among workers of tertiary educational facilities in Osun State who were adults (18 years and above). Only apparently healthy people were recruited for the study. All those who were acutely ill or had been diagnosed and/or were being managed for chronic illnesses like sickle cell disease anaemia, cancer, hypertension and diabetes mellitus were excluded. Others with disabilities that made them unable to stand were also excluded. The sample size was calculated to get an absolute precision of ± 5% using STATCALC on the Epi-Info software. The proportion of expected outcome was taken as 38.46% which was the proportion of the adults with abdominal obesity in a similar study carried out in Ekiti State, Southwestern Nigeria. [12] With an acceptable margin of error of 5%, the calculated sample size was 344, and after correcting an anticipated non-response of 10%, the sample size came to 400, who were recruited from 3 randomly selected tertiary educational institutions in Osun State using multi-stage sampling technique.
Height was measured to the nearest 0.1 meter using the stadiometer (Leceister® Height Measure, Seca, UK), weight was measured using the Seca® electronic bathroom weighing scale (SECA GmbH & Co, Germany) and waist and hip circumferences using the Gold sh brand non-elastic tape measure. The anthropometric measurements were done according to standard protocols recommended by the International Society for the Advancement of Kinanthropometry. [13] Cardiometabolic risk was assessed using WHtR, which has been shown to be the best predictor of cardiovascular risk and mortality. [14] WHtR was calculated by dividing waist circumference in cm by height in cm, and those with ≥ 0.5 were classi ed as high. Other measures of nutritional status were BMI, waist circumference, WHR and neck circumference. BMI was calculated by dividing the weight in kilograms by the height in meter 2 . Those with BMI < 18.5, 18.5-24.9, 25.0-29.9 and ≥ 30 were classi ed as underweight, normal, overweight and obese respectively. Waist circumference (in centimeters) was categorized into 3 groups for males and females into low risk, increased risk (≥ 80 cm for females; 94 cm for males) and substantially increased risk (≥ 88 cm for females and 102 cm for males). WHR was calculated as waist circumference in centimeters (cm) divided by hip circumference in cm. WHR was classi ed such that males with ratio equal to or greater than 0.9 and females with ratio equal to or greater than 0.85 had increased risk for cardiometabolic disease. The neck circumference was also used as a measure of nutritional status and was measured in centimeters.
The dietary diversity were assessed using fourteen (14) food groups, [15] and a 24 hour dietary recall. Respondents were given a score of 1 if they ate any of the food groups giving a maximum possible score of 14. The respondents were then categorized into those with Low (≤ 4), medium (5-9) and high (> 10). The physical activity was assessed using the short form of the International Physical Activity Questionnaire (IPAQ-SF), which is arguably the most widely used instrument for assessing activity. [16] This was used to classify the activity patterns of the respondents into low, moderate/medium and high.
Ethical clearance was obtained from the Ethical Review Committee, Institute of Public Health, Obafemi Awolowo University, Ile-Ife. The participants' information sheet and consent were given to them. Important information on the participants' information sheet included that the information volunteered will be kept con dential as all questionnaires were coded without names or addresses of respondents. It also emphasized that participants were free to opt-out if they were not comfortable with the information in the questionnaire. Signed consent forms were then obtained from the respondents before being recruited for the study.

Results
The mean age of the respondents was 45.8 ± 10.4 years, with a male:female ratio of 1:1.1. Most of the respondents were married (87.7%), and lived in monogamamous family settings (92.0%). Expectedly, more than half of then (53.1%) had postgradaute degrees and 53.5% earned 100,000 naira ($278) dollars or more monthly.
The mean waist-to-height ratio among the respondents was 0.53 ± 0.08, and 36.5% had values less than 0.5 (low cardio-metabolic risk) while 63.5% had values up to or above 0.5 (high metabolic risk). The mean dietary diversity score was 6.95 ± 1.50, with 4.8%, 91.2% and 4.0% having low, medium and high dietary diversity respectively. One hundred and forty-four (35.9%) had low activity patterns, while 45.3% and 18.8% had moderate and high activity patterns respectively. The prevalence of overweight and obesity were 44.0% and 25.8% respectively using the BMI categories. Using the waist circumference categories, 54.6% had increased or substantially increased risk for cardio-metabolic disease, while 63.5% had high cardio-metabolic risk using the waist-hip ratio. (Table 1)

Discussion
Previous studies have found that WHtR and WC were more signi cant predictors of cardio-metabolic outcomes than BMI, [4,17] and others have even reported that WHtR is the best predictor. [6,8,9] Therefore, use of BMI alone could lead to an underestimation of the at-risk population. Over the last several decades, efforts to prevent or treat cardiovascular diseases have resulted in the identi cation of certain cardiometabolic risks. By targeting lifestyle behaviours associated with cardiometabolic risk, it may be possible to prevent and manage risk for cardio-metabolic disease and adverse outcomes of these disease processes at the early stages of development.
The prevalence of cardiometabolic risk, using WHtR was high among the respondents, with nearly twothirds of them having high cardio-metabolic risks. A study among workers in a District Municipality in South Africa similarly reported about two-thirds of the workers having high WHtR. [18] With different studies reporting WHtR as a predictor for cardiometabolic diseases, [6][7][8][9] this nding should be a cause of worry to stakeholders in cardio-vascular health, economics, labour and productivity. This is because workers form the productive group in any society and their health should be of importance, not only to them but the Nation at large.
The other anthropometric measures of the nutritional status of the respondents further underscore the level of cardiometabolic risk among the respondents. Nearly 7 out of 10 of the workers were overweight or obese using the BMI categories and about three-fths had raised WHR and WC. This prevalence is in tandem with that reported by previous studies among workers in Ireland [19] and South Africa. [18] Thabit et al [19] in Ireland opined that this may be related to long hours of sedentary and highly stressful work related activities, compounded by poor health choices such as excessive alcohol consumption, smoking and lack of healthy dietary options within the work environment.
Results from this present study also provides evidence that waist-to-height ratio had a positive Awolowo University, Ile-Ife. The participants' information sheet and consent were given to them. Important information on the participants' information sheet included that the information volunteered will be kept con dential as all questionnaires were coded without names or addresses of respondents. It also emphasized that participants were free to opt-out if they were not comfortable with the information in the questionnaire. Signed consent forms were then obtained from the respondents before being recruited for the study

Consent for publication
Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests
The authors declare that they have no competing interests Distribution of Cardiometabolic risk according to gender and age groups