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The relationship between all cause mortality and elevated cholesterol, BMI, habitual weekly physical activity, fruit and vegetable intake and smoking status, was used to calculate risk-related age. The first step towards developing risk related age comprised of conducting a pub-med search for cohort studies published between and , which investigated the relationship between the specific risk factor and all cause mortality after adjusting for age, years of education, socio-economic status and co morbidities.

A separate search was conducted for each of the following risk factors; smoking, physical activity, fruit and vegetable intake, serum cholesterol concentration and Body Mass Index BMI. The second step involved the calculation of a pooled relative risk for each risk factor and all cause mortality.

The pooled relative risks were then entered into a mathematical model which developed to calculate risk-related age. Elevated cholesterol, being overweight or obese and smoking could lead to a 'loss' in years and higher risk-related age. Conversely, eating more than five servings of fruit and vegetables per day, and participating in more than minutes of physical activity per week leads to a 'gain' in years, and lowers risk-related age.

Participants were classified as 'at risk' for the each of the risk factors as follows;. Less than 5 servings of fruit and vegetables per day [ 10 ];. Cholesterol levels greater than 5. Blood pressure was measured using an automated sphygmomanometer. Employees were seated for approximately three minutes before being measured. Standing height cm was measured to the nearest 0. Body mass was measured using a portable calibrated scale and recorded to the nearest 0. Descriptive statistics were performed for the total sample, and separated by business sector and gender. Mean, standard deviation and standard error were calculated for all continuous variables.

Because physical activity data were not normally distributed, the median and quartile values were calculated for minimum and maximum weekly physical activity. Frequency tables were used to determine the percentage of individuals at risk, and also for the stages of change data. Bonferroni post hoc analyses were used to determine which sectors were significantly different from each other.

The relationship between demographic and clinical data and self-reported health status was investigated using Spearman's correlations. Chi-square analysis was used for the categorical nonparametric data. Chronological age and attendance were entered as covariates in all statistical analyses. All employees were invited to attend the wellness days and the mean participation for the total sample was Mean chronological age was also significantly different between sectors, with the manufacturing sector having the oldest participating employees. Both participation by the specific company and chronological age were entered as covariates in subsequent statistical analyses.

The mean BMI for the total sample was Of those tested, the mean cholesterol concentration was 4. Similar to the cholesterol results, the mean systolic and diastolic blood pressure results for the total sample The Transport sector recorded the highest number of daily servings, 3. Average, minimum and maximum time spent weekly in moderate-to-vigorous physical activity was calculated based on self reported frequency, duration and intensity.

The average time spent being physically active was The Risk-age difference was calculated by subtracting the risk-related age from the chronological age.

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The risk-age difference was similar for men and women but significantly different between the business sectors. Conversely, employees in the transport industry had significantly lower risk-age differences than the all the other sectors with the exception of consulting and finance. Mental health affected daily performance more frequently than physical health, 4. The mean number of days absent per month for the total sample was 2. Phys Health: number of days in the previous health where physical health adversely affected daily activities and performance; Mental Health: number of days in the previous health where physical health adversely affected daily activities and performance; Day away work the number of days absent from work due to ill health during the previous month.

There were significant inter-sectoral differences for self reported mental and physical health. Employees in the Engineering sector reported the highest number of days adversely affected by physical health 2. The Academic sector reported the highest number of days per month adversely affected by mental health followed by the Logistics and Engineering sectors.

Although the numbers of days adversely affected by physical and mental health were among the highest for the academic sector, these employees did not report the highest number of days absent from work. The most prevalent risk factors were low levels of average weekly physical activity and daily fruit and vegetable intake. Percentage of participants classified as 'at risk' for each of the business sectors [ 34 ]. Participants who were not physically active, nearly a third Clustering of risk factors: Percentage of Physically inactive and additive risk factors for total sample.

This study aimed to evaluate an existing wellness programme and to assess the distribution of lifestyle and clinical risk factors in an employed adult population, voluntarily presenting for health risk appraisal. Despite the low level of participation, our rates were similar to that reported in a comprehensive workplace intervention which gave employees the opportunity to participate in a variety of health promotion programmes [ 8 ].

Similar to our findings, the majority of their participants were female. A posteriori analyses was conducted in order to determine if the results differed between companies with higher response rates, compared to those with lower response rates. We divided the companies into tertiles based on participation, and then conducted an analyses of variance ANOVA to determine if there were significant differences in the health and behaviour profile according to levels participation. There were no significant differences in age, both chronological age and risk-related age, Body Mass Index BMI , cholesterol concentration, and habitual levels of physical activity in the high versus the low responders.

Conversely, the companies with the highest response rates had significantly higher blood pressure, more total risk factors for NCD and lower daily fruit and vegetable consumption than those with the lowest response rates. Thus the wellness days in the companies with the highest attendance seemed to be attracting employees at increased risk of non-communicable diseases.


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It is therefore important to address attendance and uptake in worksite-based programmes. This is supported by Kwak et al who advocates the reporting of participation rates in order to correctly interpret results and implications of the research findings [ 9 ]. It has been previously demonstrated that the success of recruiting employees in health risk screening is influenced by the interest shown from the company's management, as well as, internal advertising and marketing strategies [ 21 , 22 ].

In these 18 companies, low levels of participation may be a reflection of poor marketing and advertising prior to the wellness days. The poor uptake could also be attributed to availability of staff on the wellness day, which was only offered approximately once per year.

For example, the transport sector comprised of airline companies, and the low level of participation may be in part due to the fact that some staff was not available on the wellness day. The solution in this case, would be to offer the health and wellness events on more than one day per year in order to attract more participants.

Since one of the aims of these wellness days is to offer individuals an opportunity to determine their health status, particularly those at increased risk, the advertising plays an important role in attracting as many volunteer participants as possible. Leslie et al. Other factors which could increase participation is the provision of incentives [ 24 ] and also the establishment of employee advisory boards who have management involvement, a level of autonomy and also company commitment [ 25 ]. Therefore, the recruitment for wellness days, particularly if they are only one-day events, should begin earlier than the one-week time period used in the current study and should also consider including direct contact with the employee.

Participation in workplace based interventions which include health risk assessments, has also been associated with decreased short term disability days away from work [ 26 ]. The potential benefits of increasing participation would therefore include future costs associated with absenteeism and training temporary personnel. Bias in interpretation was subsequently addressed by adjusting inter-sectoral comparisons for percentage participation in the health risk appraisal.

The second important finding in our study was that risk-related age was significantly higher than chronological age and this risk-age difference was greatest in the Manufacturing sector. The risk-related age is a reflection of the presence of risk factors such as smoking, inadequate physical activity and fruit and vegetable intake, elevated cholesterol and a BMI greater than These are all modifiable risk factors, and comprehensive interventions may reduce risk-related age and possibly result in a 'gain' in years [ 27 , 28 , 8 ].

The inter-sectoral differences may be used by health insurers in identifying companies which are likely to benefit most from intervention programmes. Improved health status and lifestyle habits has been associated with reduction in health care costs, increased productivity and decreased absenteeism [ 29 , 28 , 8 ]. These findings are supported by Serxner et al.

This research study is among the few in South Africa SA which allows for the comparison of the health status of the corporate sector to that of the general SA population. This is due in part, to the fact that the South African Demographic Health survey was recently completed in — Secondly, measures were, in some instances, comparable, due to the similarity of definition of risk factors and risk questionnaires between the two surveys, as well as risk cut-points.

For example, the men in the present study had a higher prevalence of overweight and obesity compared to the general male population [ 2 ]. Conversely, women in the present study had a lower prevalence of overweight and obesity, compared to that of the SADHS. The differences between the employed adults and general population may be due to differences in educational and socio-economic status.

The SADHS reported that the prevalence of overweight was highest among men in urban settings and those who were educated [ 2 ], which reflects the participants in the current study. In addition, SAHDS showed that women with the lowest levels of education were the most obese [ 2 ], while most of the women in our study had some form of higher education. Furthermore, the individuals screened as part of this study report lower levels of participation in physical activity than the general population.

This has important implications since physical activity is associated with decreased risk of disease, but also, with greater levels of productivity and lower rates of absenteeism, which is important in the corporate sector [ 14 ]. Indeed, our results showed that those with higher levels of weekly physical activity reported significantly fewer days away from work the previous month.

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Even only one day of physical activity per week was associated with significantly reduced absenteeism compared to those employees who were inactive, and further reductions were observed when comparing 2 days to one day of physical activity [ 14 ]. Data from the 'StayWell' programme showed that employees with 4 or more risk factors were 1. Our study corroborates these findings where those with a higher number of risk factors had significantly more days away from work, and also more days with performance adversely affected by poor mental or physical health.

Therefore, it is likely that reducing the number of risk factors will have important implications in worksite settings, reducing both the direct and indirect costs associated with absenteeism.

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Clustering of risk factors has also been associated with diseases such as hypertension, heart disease and diabetes [ 30 ]. These results suggest that increasing habitual physical activity may positively impact on the other risk factors, and subsequently lower the overall risk profile of individuals.

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Indeed, previous research has suggested that physical activity may act as a catalyst and entry point for improving diet and stopping smoking [ 10 ]. Reductions in risk factors that could therefore potentially be achieved by increasing habitual physical activity could decrease the risk of morbidity and mortality [ 26 ]. In addition, by decreasing the total number of risk factors, the total number of days absent from work can also be decreased [ 27 ]. The health risk assessment has been regarded as an entry point in comprehensive health promotion programmes and precedes the implementation of targeted interventions [ 31 ].

Completing a self-reported questionnaire such as the one used in our study to determine the prevalence of risk factors and to calculate risk-related age, may increase an individual's awareness of risk factors and aspects of their life that could improve.

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This increased awareness could be the first step in initiating change and improving health status, and risk-related age. Pelletier et al administered an online health risk appraisal on behalf of a health care provider to employees at baseline and again one-year later [ 32 ].


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  7. No other interventions were reported in their study, yet there were significant risk reductions observed for dietary habits, elevated serum cholesterol, and non-significant reductions in inactivity and BMI [ 32 ]. The potential health and cost benefits that can be obtained by following up the health risk assessment with an intervention could be greater than by only offering screening activities.

    Thus, interventions could be targeted successfully at those categorised as 'high risk' or 'moderate risk' [ 31 ] since those in the higher risk categories could show greater improvements in health [ 12 ]. Another important finding in our study was there was a knowledge-behaviour "gap", with a large percentage of employees believing that their dietary habits were healthy, despite consuming less than the recommended 5 servings of fruit and vegetables per day.

    This is supported by Cook et al's findings where a higher nutrition knowledge score was associated with increased vegetable intake, and belief in healthy nutrition was reflected with increased fruit consumption [ 33 ]. Health risk has been associated with both increased presenteeism and absenteeism [ 32 ]. Thus, another noteworthy finding from our study was that the total number of days adversely affected by poor mental or physical health was less than the number of days away from work.

    These results may provide an indirect indication of presenteeism, suggesting that the employee is at work, but experiencing low levels of productivity. It has been widely established that health and well-being impact on work performance and job satisfaction [ 34 ]. Another important outcome of this study was that it allowed for inter-sectoral comparisons for risk factors and self reported health status. There were significant differences for each of the health and lifestyle measures among the various sectors. However, no single sector consistently emerged as having the healthiest or least healthy employees.


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    5. Consequently, intervention strategies should be based on the individual requirement or health status of the various sectors or companies. The main limitation of this study is that employees volunteer to participate in the wellness days, thus our results may be biased towards those willing to participate.

      However, Goetzel et al. We acknowledge that this was an opportunistic study, evaluating an existing wellness programme. However the findings do provide some insight into the health profile of the South African corporate population, and underscores the need for further, and more representative research. Despite a decreased risk for non-communicable disease based on chronological age among the participants in our study, their risk is increased based on the presence of other risk factors such as inactivity and increased BMI.

      Furthermore, based on the higher rates of overweight and obesity, smoking and inactivity; men presenting for worksite wellness days may actually be less healthy than the general SA public. The relationship for women is slightly different, since they have a lower rate of overweight and obesity and smoking than that shown in the SADHS, but they have much higher levels of inactivity. This has important health and economic consequences, and underscores the importance of implementing strategies and interventions aimed at improving the health status of employees.

      Intervention programmes targeting these risk factors would therefore play an important role in improving the health profile of employees. Discovery Health funded the data collection component of the study, especially since it forms part of their corporate offering. TLK—A was involved in the conception and design of research study, data cleaning and analysis, and also in drafting and writing manuscript.

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      CB assisted with data collection, and also the cleaning and analysis of some of the data, and in the writing and editing of the manuscript. CN worked for the health insurance company and played a role in collecting and collating the health risk assessment data and acquisition of health related claims, and also edited the manuscript. LD worked for the health insurance company and played a role in collecting and collating the health risk assessment data and acquisition of health related claims, and also edited the manuscript.

      TDN played role in critically revising and editing the manuscript. EVL was involved in the conception and design of research study, assisted and guided the statistical analysis, in the writing and editing of the manuscript and also the general management of the research team. Ms Kate Cowling for contributing to the development of the "risk related age model".

      Source of funding — University of Cape Town. Mr Jaco Conradie who de-linked all the health and wellness day results and also the medical claims data and then sent to the researchers Source of funding Discovery Health. The biokineticists and allied health professionals who conducted the wellness days and collected all the data on behalf of Discovery Health Source of funding: Discovery Health. Discovery Health Vitality also provided the researchers with un-linked data for analysis. The University of Cape Town is not constrained in any way by the funder and is free to publish all results of the research study.

      National Center for Biotechnology Information , U. BMC Public Health. Stuart is the editor-in-chief of Engage Me Online. After pursuing an MA in South African literature, he spent five years reporting on the global technology scene. Intrigued by the intersection of technology and work, he joined Engage Me as the editor-in-chief. He is a passionate runner, training for his first ultra marathon. Enter Password Confirm Password. Subscribe to our newsletter? Make it snack-sized.

      You might have a bigger problem on your hands. Think again. Go into any newsroom. A much better approach is to integrate CSR and employee wellness. Use the skills you have For many companies, getting employees involved in CSR involves getting everyone to do some menial volunteer work at a charity.

      Good questions, great answers Perhaps the most important thing you can do when it comes to integrating employee wellness with CSR though, is to consult your employees. Inform Me Hands on or off: Why letting employees fail is key to t Inform Me Dishing out tough love: how to give unfavourable feedba Stay relevant and up-to-date with intriguing stories, cutting-edge trends and inspiring people. Sign-up to our weekly newsletter now!