Health Profile of Australian Employees

Transcription

1 Prepared by the Centre for Health Initiatives for the Workplace Health Association Australia Ms Laura Robinson, Dr Christopher Magee, Mr Murad Safadi and A/Prof Rajeev Sharma December 2014

2 Contents Executive Summary... i Introduction... v Methods... 1 Section 1. Sample characteristics and a snapshot of employee health... 2 Section 2. Trends in Health ( )... 3 Biometric Health Outcomes... 4 Behavioural risk factors... 8 Smoking... 8 Alcohol consumption... 8 Physical activity... 9 Mental health Stress Psychological Distress Section 3. Differences in Health Outcomes by Gender and Age Biometric Health Outcomes and Gender Behavioural Risk Factors and Gender Mental health and gender Differences in Health Outcomes across Age Groups...15 Behavioural risk factors and age groups...15 Mental health and age groups Section 4. Health Outcomes by Interventions/Health Checks and Sources Section 5. Comparisons between intervention outcomes with the broader international data Recommendations References APPENDIX A. DEFINITIONS APPENDIX B. SAMPLE CHARACTERISTICS AND A SNAPSHOT OF EMPLOYEE HEALTH APPENDIX C. TRENDS IN HEALTH ( ) APPENDIX D. HEALTH OUTCOMES BY GENDER APPENDIX E. HEALTH OUTCOMES ACROSS AGE GROUPS

3 APPENDIX F. INTERVENTION TYPE/HEALTH CHECK APPENDIX G. HEALTH OUTCOMES BY SOURCE APPENDIX H. CORE ITEMS

4 Executive Summary The aim of this project is to examine the health profile of a sample of Australian employees. This report presents the outcomes of the integration of employee health data from five organisations (members of WHAA) who participated in this project. Objectives of this report are 1 : 1. To document the risk factor prevalence and lifestyle data of working Australians according to their demographic factors; 2. Where possible, to compare these data to current normative data sets; 3. Where possible, to link changes in risk status to the type of intervention offered; 4. Where possible, to compare intervention outcomes to the broader international data on program outcomes and design; 5. To identify a common core of items that should be included in all WHAA assessments to facilitate future research related to the impacts of HRA assessments and related feedback/counselling; and 6. To propose an option for WHAA members to have certain Health Risk Assessment (HRA)-related data (biometric data initially) stored centrally and later combined with data from other WHA members to facilitate ongoing research on HRA topics of importance to WHAA members. Methodology Deidentified data were provided to CHI from five member organisations in Microsoft Office Excel format. Data were cleaned and merged, with data entered into SPSS (version 19) for statistical analysis. The table below shows the sample sizes (N) for the period from 2004 to The sample sizes varied across the period with the smallest sample in 2014 (n=2440) The extent to which these objectives have been met was dependent on the quality of the data available and the extent to which the data could be combined across the databases and quality of datasets. 2 Data were received.;mid-way through 2014, therefore this is an incomplete data set i

5 Key Findings Characteristics of the sample were: o Ages ranged from 16 to 81 years (mean=41.7 years), with the majority of workers aged from 25 to 54 years; o Males were usually over-represented compared to females. A snapshot of health in 2013 indicated the following findings: o About 1 in 10 (12.0%) workers had high blood pressure; o Nearly a quarter (23.8%) had high cholesterol; o More than half were overweight or obese (40.3% and 20.2%, respectively); o Abdominally overweight or obese was higher in males (46.1%) than females (37.0%); o Around 11% were daily smokers or consumed alcohol at a risky level; o Approximately half were physically inactive; o 65.1% of employees reported moderate to high stress levels, and 41% had psychological distress levels considered to be at-risk. When examining health trends across the 10-year period, the following areas showed that health became better over time: o Blood pressure; o Abdominally overweight or obese; o Daily smoking. Outcomes that deteriorated or became worse over the 10-year period included: o Body Mass index, which increased to slightly above the national rate (64.1% compared to 63.2%); o Physically inactive workers peaked at 60%, above the national rate of 56%; o Psychological distress fluctuated (30% to 40.1% prevalence), however remained consistently above the national rate (29.9%); o A consistently high proportion of workers indicated moderate to very high stress levels from 2004 to 2014 (between 60 and 70%). There were differences in health outcomes by gender. o Males had greater rates of high blood pressure/hypertension, BMI, waist circumference, and alcohol risk, o Females were at greater risk of experiencing high psychological distress. Health outcomes differed across age groups, with findings showing: o Three in four people aged between 25 and 64 years had moderate to high levels of stress; o BMI, blood pressure/hypertension and cholesterol all increased with age; o Younger groups were more likely to be current smokers, and those aged between 45 and 54 years most at risk of drinking alcohol at risky levels. Limited intervention information showed some significant differences in overweight and obese (BMI) and high cholesterol between health checks ii

6 Where possible, health outcomes were compared between origins of source, and showed that there were significant differences between body mass index, blood pressure, and total cholesterol. Strengths and Limitations This study provides a novel insight into the Australian working population, and has a number of strengths, including: Large sample size; Multiple organisations; Data across 10 years; Various indicators of health, including both mental and physical health are captured. Several limitations of this study need to also be acknowledged. These include: The data were unable to be matched across time, thus interindividual change was not captured; Health outcomes were measured inconsistently at times across years and organisations; Intervention detail was lacking or incomplete; Work-related variable details were also lacking, for instance, work hours and management level. Recommendations The following recommendations are provided to aid future work in this area. In particular, it is recommended that: Core items are identified for future data collection; A data integration process is implemented to minimise errors and provide data consistency and ease of collection and management; Information on employee absenteeism, demographic variables and other workrelated information is also recorded; Intervention data is included so that any changes relating to interventions can be captured and comparisons between interventions may be made; Data are coded to allow matching over time; Regular analysis and cleaning of data to reduce complexity of task compared to more occasional analysis; and Periodical reports on findings are made to the WHAA board and to member organisations. iii

7 Conclusion The results of this project indicate some positive trends in health outcomes over the 10- year period. These changes may be attributable to HRAs and other workplace health strategies; however, more research is needed to confirm this conclusion. Some health outcomes most notably physical activity and mental health were less positive. Poor mental health, for example, was reported by 40% to 60% of employees. This suggests that organisations need to continue efforts to create mentally healthy workplaces. iv

8 Introduction The purpose of this project was to examine longitudinal data provided by WHAA member organisations on the health and well-being of their employees. This involved addressing the following specific objectives: 1. Describe the health characteristics of working Australians, primarily in terms of biometric data; 2. Identify demographic and work-related factors associated with health outcomes; 3. Explore whether workplace interventions are associated with health outcomes; and 4. Provide recommendations regarding the future collection and management of data from the WHAA members. This report begins by describing the method and analysis used. It will then go on to present the findings and address the stated objectives in the following sections: 1. Sample characteristics and a snapshot of employee health; 2. Trends in health ( ); 3. Differences in health outcomes by age and gender; 4. Health outcomes by interventions/health checks, and sources; 5. Comparisons between intervention outcomes with the broader international data; Next the strengths and limitations are reported and, finally, overall recommendations are. This study covered a large volume of data and in order to maximise the readability of this report findings are reported in a brief format throughout, with more comprehensive information, including tables and figures were appropriate, are available in the Appendices. v

9 Methods WHAA member organisations were invited to provide available employee health-related data. A total of five organisations provided data to CHI. As would be expected, the datasets provided varied in terms of format, variables included, and timespan. This required substantial database management and cleaning of data in order to merge the datasets into a single database that was suitable for analysis. Despite some inconsistencies, there was generally sufficient data to be able to meaningfully examine trends in health-related outcomes over time. Most organisations provided detailed data for the preceding 5 years; some organisations provided data up to 10 years ago (and beyond) however at times there was often not sufficient data to examine trends over this time period. Therefore, results presented below relate to a 5-year period ( ), or a 10-year period ( ). In examining trends in health-related outcomes over time, we referred to corresponding health data from the general Australian population. This involved drawing on data from sources such as the Australian Bureau of Statistics (ABS) and the Australian Institute of Health and Welfare (AIHW) (e.g. the Profiles of Health, Australia report, 2013, from the ABS, and the 2014 Australia s Health report from the AIHW). Health-Related Outcomes Specific details on how these outcomes were defined and quantified are provided in Appendix A. 1

10 Section 1. Sample characteristics and a snapshot of employee health Sample Characteristics Valid records of 28,743 employee records with complete data were available across the 5 to 10 year period. Sample size varies throughout report due to missing data. Ages ranged from 16 to 81 years, with an average of 41.7 years. The majority of workers were aged between 25 and 54 years, and this range is consistent with National data (AIHW, 2014). In general, there were slightly more males then females, which is consistent with the gender representation in the Australian workplace, where there is a greater proportion of males than females (Workplace Gender Australia, 2014). A snapshot of employee health The 2013 data are (n=6903) used to report the current risk factor prevalence and lifestyle data of working. An overview of findings is presented here with further detail available in Appendix B. Biometric Health outcomes Approximately 1 in 10 reported high diastolic blood pressure (12.9%) and high systolic blood pressure (12.0%). Nearly 1 in 4 reported (23.8%) high cholesterol. More than half of the sample was considered overweight (40.3%) or obese (20.2%). Abdominally overweight or obese prevalence was 37.0% in females and 46.1% in males. Behavioural Risk Factors Daily smokers comprised of 11.5% of the 2013 sample, and slightly fewer (11.2%) consumed alcohol at a risky level. Meanwhile nearly half (48.8%) were considered physically inactive. Mental Health Stress and psychological distress were considered when exploring mental health of employees. Moderate to high stress levels were reported in 65.1% of employees surveyed in 2013, and 41.1% had psychological distress levels that are considered at-risk. 2

11 Section 2. Trends in Health ( ) Data on trends in health-related outcomes are summarised below, arranged according to biometric health outcomes and health risk factors. For each health-related outcome, we provide a brief description on the outcome, show trends in the outcome over time, and compare the trends with relevant population health data. In general, the results indicate that the proportion of individuals with high blood pressure and high cholesterol declined over the 5 year period from 2010 to There was also an increase in the percentage of individuals classified as having a normal body mass index. Fewer individuals are engaging in potentially detrimental behaviours such as daily smoking as excessive alcohol consumption. Mental health trends were less clear and tended to fluctuate across the years. However rates were consistently higher than the Australian figures. More detail is available in Appendix C. 3

12 Biometric Health Outcomes High blood pressure/hypertension Employee Trends: Overall the prevalence of high blood pressure declined between 2010 (30.0%) and 2014 (15%). There was a slight peak in prevalence in 2013 (18.4%). 35% 30% 25% 20% 15% 10% 5% 0% National Figure 1. Proportions of high blood pressure/hypertension between 2010 and 2014 Comparisons with Population Data: Data on high blood pressure in the general population were obtained from the Australian Institute of Health and Welfare (AIHW, 2014). These data indicate that high blood pressure prevalence in Australia is 32%, with a greater prevalence in men (34%) than women (29%) (AIHW, 2014). The prevalence has remained mostly stable, around 30%, over the past 15 years (AIHW analysis of AusDiab study). As shown in Figure 2, the rates of high blood pressure levels were consistently lower in the employee sample than the general population. 4

13 Cholesterol Employee Trends: As shown in Figure 2, the prevalence of high cholesterol fluctuated across 2010 to 2014, with the highest rate in 2014 (26.7%). The lowest prevalence was evident in 2012 (21.1%). 35% 30% 25% 20% 15% 10% 5% 0% National Figure 2. Prevalence of high cholesterol between 2010 and 2014 with national data Comparisons with Population Data: Population data on cholesterol were obtained from the Australian Bureau of Statistics. These data indicated that in , 32.8% of the adult Australian population had abnormal or high total cholesterol levels (ABS, 2013a). This is a lower prevalence than in (48%) (ABS 2013a). As seen in Figure 3, cholesterol levels of study participants were substantially and consistently lower than the national data between 2010 and Body Composition We examined two measures of body composition: Body Mass Index (BMI), and waist circumference. i) Body Mass Index (BMI) Employee Trends: As shown in Figure 3, the BMI of individuals surveyed fluctuated over the years, however the proportion in the overweight category increased steadily to 2010 (36.3%) when the rate slowed. The obesity rates also fluctuated, although the rate of growth appears to slow to 2014 (42.4%). 5

14 % Health Profile of Australian Employees Overweight Obese Figure 3. Body Mass Index (BMI) between 2004 and 2014 with the national data Comparisons with Population Data: Population data on BMI were derived from the AIHW (2012). As shown in Figure 4, employees had similar rates of overweight and obesity compared with the general population. ii) Waist circumference Employee Trends: The average waist circumference for females ranged from a high of 83.4 cm in 2011 to a low of 78 cm in These figures are below the at-risk cut-off of 85 cm. The average waist circumference for males ranged from a high of 94.7cm in 2010 to a low of 82.8 cm in The prevalence in females tended to fluctuate over the years, whereas the overall trend for males was an increase. Comparisons with Population Data: Population data on waist circumference were derived from the Australian Bureau of Status (2013b). About 66% of Australian females and 60% of Australian males are overweight or obese based on waist circumference measures. The rates of overweight and obesity in the employee sample were consistently lower than the general population. 6

15 Summary of biometric trends High blood pressure prevalence fluctuated during the 10-year period, however overall rates declined. Levels remained below national figures. High total cholesterol showed an overall increase to the year 2014, however remaining below national levels. The proportion of overweight and obese people increased slightly between 2004 and 2014, and is above the national average. Overall trends for abdominally overweight and obese males and females remained below national rates. 7

16 % Health Profile of Australian Employees Behavioural risk factors Smoking Employee Trends: As shown in Figure 4, the proportion of current smokers decreased between 2004 and 2014 (from 20.5% to 10%). The results clearly indicated a decline in smoking rates Figure 4 Smoker status and national data between 2010 and 2014 with national data Comparisons with Population Data: The National data were drawn from the 2013 National Drug Strategy Health Survey (AIHW, 2013). The proportion of current smokers aged 14 and over was 15.8%. In the employee sample, rates of smoking were consistently lower than the population data. Alcohol consumption Employee Trends: The lifetime risk of harm from alcohol consumption fluctuated from 12.1% in 2004 to a peak of 15.5% in The prevalence then tended to decrease, and remained below the national prevalence (20%) during this period (Figure 5). 8

17 % Health Profile of Australian Employees Figure 5. Proportion at a lifetime risk of harm from alcohol consumption between 2010 and 2014 with national data Comparisons with Population Data: Population data were sources from the AIHW (2014). Based on the 2009 NHMRC guidelines about 20% of Australian adults drink at levels that place them at risk of lifetime harm (AIHW, 2014). This rate has not changed substantially from In employees, the rate of alcohol risk was substantially lower than population data. Physical activity Employee Trends: Overall the proportion of workers with inadequate aerobic activity or no regular exercised declined between 2004 and 2014 (from 64.0% to 46.1%). This is despite a peak in 66.5% in Comparison with Population Data: The National physical activity data were drawn from the Australian Health Survey: Physical Activity, (ABS, 2013a). Figures were overall greater than the national prevalence of 56%. This indicates that levels of inadequate exercise in the employee sample was higher than the national data (ABS, 2011). 9

18 Summary of behavioural risk factors trends The prevalence of smoking decreased over the ten-year period and remained below the national average. A lower proportion of individuals were classified as drinking at a lifetime risk level in 2014 than in 2004, although rates did rise between Physical inactivity rates fluctuated, peaking in Rates in most years were around the national prevalence. 10

19 Mental health Stress Employee Trends: Moderate to very high stress levels fluctuated across the 10 year period, ranging between 58 and 71.8%. The lowest rate was recorded in 2014, however the data were incomplete in that yearn which may contribute to the lower results. Comparison with Population Data: National data was not compared due to the difficulty defining stress and insufficient information available on the type of stress measured made comparisons with population data difficult. However, recent figures show that about 75% of Australian workers believe that workplace stress is affecting their health (Casey, 2013). Psychological Distress Employee Trends: Over a six-year period ( ) 3, psychological distress levels fluctuated, with the proportion in the implement lifestyle strategies or recommend to GP categories peaking at 40% in 2011 and dropping to 36.2% in Comparison with Population Data: National data indicates that approximately 30% of Australians experience moderate to high 4 psychological distress. The employee rate is greater than reported levels in the current population for all years except 2009 (30.1%). Summary of mental health factors trends Overall, moderate to very high stress levels ranged from 58% to 71%. Moderate to high psychological distress fluctuated slightly across the time period, however remained above national rates. 3 Data on psychological distress prior to 2009 were not available 4 Moderate is equivalent to recommend lifestyle strategies and high to recommend to GP 11

20 Section 3. Differences in Health Outcomes by Gender and Age The purpose of this section is to examine age and gender related differences in health outcomes in the employee sample. More details are available in Appendices D (by gender) and E (by age). Biometric Health Outcomes and Gender Cholesterol and gender The rates of high total blood cholesterol were similar for males (24.2%) and females (23.6%), and this trend is consistent with National data. However the high cholesterol rates in the current study were notably lower than National rates. Blood pressure and gender Statistically fewer females than males reported high blood pressure levels (6% to 17.3% for systolic and 8.4 to 16.9% for diastolic) (χ 2 =17.4, p<.001). This differences is consistent with national data which also shows males at greater risk of high blood pressure (34.1% compared with 29.1% respectively). The national prevalence was however substantially greater than our findings. Body Composition and Gender Body Mass Index (BMI) and gender The proportion of overweight or obese females was statistically significantly (p<.001) lower than and males (48% compared to 71.9%). The prevalence in females was lower than the national data (55.7%), and the prevalence in males was similar to national data (70.3%). Waist circumference and gender A statistically significantly (p<.001) greater proportion of males (77.0%) than females (42.1%) had waist circumference that placed them in abdominally overweight or obese categories, and at increased risk for developing chronic disease. Both rates differed somewhat in comparison with population data (66% females and 60% males). Behavioural Risk Factors and Gender Smoking and gender There were minimal differences in females and males reporting current smoking (10.9% compared to 12.4% respectively), and these proportions were substantially lower than the national figures (16.3% compared with 20.4%). 12

21 Alcohol and gender A statistically greater proportion of males than females exceeded the current alcohol guidelines (18.2% compared with 5.7% respectively, (χ 2 =39.0, p<.001). This is consistent with national data which shows greater levels of risky drinking in males than females nationally. However, it is worthwhile noting that national prevalence are greater than the current findings (29.1% compared to 18.2% for males, and 10.1% compared to 5.7% for females, respectively). Physical activity and gender There was little difference in the proportion of females (65.2%) and males (67.7%) reporting inadequate levels of physical activity. The rate for females is lower than the national proportion (65.2% compared to 72.4% nationally), and higher for males than the national proportion (67.7% compared to 61.3%).. Fruit and vegetable intake and gender A greater proportion of males than females report not consuming fruit or vegetables every day (7.6% compared with 3.9% respectively). The proportion of males was slightly greater than the national data (6.6%), whilst the proportion of females was slightly lower (4.5%). Mental health and gender Psychological Distress and gender Greater proportions of females than males (41.9% compared to 35.2%, and 3.4% compared to 2.1%, respectively) were in the categories of implement lifestyle strategies and recommend to GP. These differences are similar to the national figures with higher distress levels in females than males (Casey, 2013). Stress and gender Reported stress levels were similar for males and females. More than half of males (52.9%), and nearly a half of females (47.2%) reported moderate stress levels. Meanwhile, 17.4% of females and 18.7% of males reported high stress levels. 13

22 Summary of gender differences Across the biometric indicators, (cholesterol, blood pressure), males were more likely than females to be considered at-risk. There were no differences for risk factors such as smoking and physical activity. However a greater proportion of males than females exceed alcohol guidelines. Females showed higher psychological distress levels than males however stress levels were similar between genders 14

23 Differences in Health Outcomes across Age Groups BMI and age The greatest proportion of individuals in the normal BMI range were aged between 16 and 24 years, followed by 25 and 49 years. This differed for the overweight range where the greater proportion of individuals were aged more than 65 years, followed by 50 to 65 years. The increase in proportion of overweight individuals with age is consistent with national data. Blood pressure and age There was an increase in the proportion of individuals reporting high systolic blood levels and those reporting high blood pressure as age increased. There was an exception in the over 65 years group where high diastolic prevalence became less common with increasing age. Cholesterol and age High blood cholesterol increased with age up to 65 years. This trend is consistent with national data (AIHW). Behavioural risk factors and age groups Smoking and age The rate of smoking was highest in 16 to 24 year olds (24%) who smoked more than any other age group. This rate is slightly higher than Australian data of about 18% (ABS, 2013b). It is important to note however that the data are categorised slightly differently for National data (ABS, 2013) and may account for some of these differences. This report was limited by the categories provided in the data gathered. Alcohol and age When examining those considered to be drinking alcohol at-risk levels, the greatest proportion were aged between 45 and 54 years (55.3%), followed by 25 to 34 years (24.2%). None of those age 65 years and over were consider consuming alcohol at risky levels. Physical activity and age Moderate physical activity ranged from a low of minutes per week in year olds to a high of minutes in year olds. Intense exercise was the greatest in year olds (147.8 minutes/week) and the lowest in year olds (99.1 minutes per week). 15

24 Fruit and vegetable intake and age Respondents in the 35 to 54 year age group were the most likely to report they did not consume it daily (52.8%). This was followed by those aged between 25 and 34 years (32.5%). Mental health and age groups Psychological Distress and age Nearly 50% of individuals aged from 16 to 24 years reported moderate to high psychological distress (coded as either recommend lifestyle strategies or recommend to GP in survey). This rate is greater than the national rate of 48.1% (ABS, 2012). Consistent with national data, the rates of moderate to high psychological distress decline with age to about 34% in individuals aged 65 years and over. Stress and age Greater proportions of 35 to 54 year olds (21.8%) and 55 to 64 year olds (18.2%) reported high stress levels than younger people. Approximately 75% of Individuals aged between 35 and 64 years indicated moderate to high stress levels, and these rates were broadly consistent with the national data. Summary of differences across age groups The greatest proportions of overweight and obese individuals were aged 5o years and over. Blood pressure increased with age One in four 16 to 24 year olds are current smokers 45 to 54 year olds had the highest levels of alcohol consumption Nearly 50% of 16 to 24 year olds report moderate to high distress About 3 in 4 workers aged between 35 and 64 years report moderate to high stress levels. 16

25 Section 4. Health Outcomes by Interventions/Health Checks and Sources Health outcomes by intervention/health check Data were compared by key health outcome indicators across health assessment types (where available). Whilst various interventions or health checks were conducted, information on these were limited. There was, however, information on some health checks and these will be discussed here. Included health checks are shown in Figure 6, which shows a range of biometric, lifestyle and mental health outcomes. There was significant gender differences across types (p<.001). A greater proportion of males (66.5%) than females (33.5%) underwent a LifeCheck Executive assessment (see Figure 6 below for details), and a greater proportion of females (64.7%) than males (35.3%) underwent a Life Check assessment. Differences were also evident across a number of health outcomes. For instance, BMI outcomes, greatest proportion of obese and overweight in the Life Check Executive type (68.2%) and the lowest proportions in the Healthy Heart type (53.1%). High systolic blood pressure differed significantly (p<.001) across types. A greater proportion of employees who took part in the LifeCheck Executive (17.5%) reported high systolic blood pressure, whilst those who were part of the LifeCheck assessment reported the lowest rate (6.8%). Finally, more than one in four workers who were in The Mini (26.7%) assessment type reported high blood cholesterol levels, and slightly fewer the Essentials type (24.3%). The lowest rate of high cholesterol levels were in the LifeCheck Executive assessment type (13.7%). 17

26 Health outcomes by source Figure 6. Health Check Features Data were provided from different organisations and coded as sources. Differences between sources in terms of health outcomes were examined, and some significant differences were identified. There was little difference in age and gender across sources. However, Body Mass Index (BMI) did vary significantly across the three sources, with individuals from Source 3 having a substantially lower proportion of overweight obese workers. Both high systolic and diastolic blood pressure rates differed significantly across sources, with Source 1 having substantially lower rates than Sources 2 and 3. Finally, total cholesterol levels were compared between Source 2 and 3 (due to missing data from Source 1), and findings show that Source 2 had a significantly greater proportion of high cholesterol than Source 3. Differences between sources were not tested for all health outcomes and behaviours (such as psychological distress and alcohol consumption) due to missing data. 18

27 Section 5. Comparisons between intervention outcomes with the broader international data Approach A brief review of the literature was conducted to identify international data on intervention outcomes. The search strategy covered a number of medical, psychological, health and multidisciplinary databases (such as ProQuest, Scopus, ScienceDirect ). Search terms included, but not limited to: workplace health, interventions, employee, mental health, physical health, blood pressure, cholesterol. Australian-based studies were excluded from the search. Results of interventions and comparisons need to be interpreted with caution for a number of reasons. These include inconsistent evaluation techniques and coding of variables across studies, various sampling methods, influences of characteristics of the sample, quality of study and possible selection bias. Despite these limitations, comparisons can offer insights into broader international intervention program designs and outcomes in the workplace health field. Cholesterol and blood pressure Multi-component interventions target various behaviours and outcomes. There are mixed results associated with these interventions. For instance, a 12-month environmental intervention in the Netherlands targeting physical activity in order to reduce cholesterol, BMI and blood pressure was found to be ineffective in office workers (Engbers et al., 2007). Conversely an earlier study in the USA examined the behavioural and clinical impact of a worksite chronic disease program targeted at intensive lifestyle changes was effective. Significantly lower body fat, blood pressure and cholesterol were reported by those involved in the intervention (Aldana, et al., 2005). Comparisons with interventions A review of past interventions shows inconsistent results in regards to reducing cholesterol and blood pressure. Current data showed a reduction in cholesterol but a rise in blood pressure. This indicates that the role of interventions on improving blood pressure and cholesterol fluctuates and is not clear. Physical activity and weight control Interventions targeting increased physical activity were effective. Intervention designs included increased awareness through health promotions and environmental rearrangements (Naito, Nakayama et al., 2008, Japan), which found a beneficial change in serum HDL-cholesterol. Meanwhile a worksite physical activity program in the 19

28 Netherlands found a positive effect on physical activity and musculoskeletal disorders (Proper, et al., 2003). Similarly a review also in the USA (Anderson, et al., 2009) of various worksite nutrition and physical activity programs promoting healthy weight among employees suggested some effectiveness of this approach. There was modest improvements in bodyweight at 6 and 12 month follow ups. Finally, a review by Katz et al. (2005) of weight control interventions including education, group activity, cognitive techniques and diet changes were found this multi-component approach to be effective in controlling overweight and obesity. These interventions were both effective in increasing physical activity and aiding in weight control. Comparisons with current data Data collected over the past 10 years shows a slight and steady increase in BMI. Although prevalence of obesity and overweight remained below National levels, the effects of the reviewed interventions were not evident. In terms of physical activity, data in this report showed a reduction in the proportion of workers who were getting inadequate exercise. This is consistent with the studies reviewed where physical activity increased, suggesting that targeting physical activity in the workplace can produce positive results. Alcohol A 6-month controlled worksite prevention trial in the USA found that those in the intervention group were significantly more likely to reduce their drinking frequency than those in the control group (Anderson & Larimer, 2002). Also, alcohol-related negative consequences reduced among female problem drinkers in the intervention group. This intervention was effective in minimising harmful drinking behaviour Comparisons with current data The reduction in harmful drinking found in the current data is consistent with findings from the reviewed interventions where harmful drinking behaviour declined. Smoking A meta-analysis by Smedslund et al., (2004, Norway) found that workplace interventions appeared to reduce smoking initially, however the effect reduced over time to be absent by 12 months. Interventions included self-help manuals, incentives, competitions, physician advise and health education. Comparisons with current data 20

29 The proportion of current smokers declined over the 10-year period. This is inconsistent with findings from the meta-analysis by Semdslund et al., (2004, Norway), where the effect of the intervention was not present after 12 months. 21

30 Strengths and Limitations This project provides a preliminary insight into the health of a large sample of Australian employees. Although the findings are meaningful, there are some limitations. These are primarily related to the challenge of integrating data from multiple sources, where there are, at times, differences in format, variables, and measurement. Some of the main strengths and limitations are outlined below. A series of recommendations are then provided to guide future data collection, management, analysis and reporting. This study provides a novel insight into the Australian working population, and has a number of strengths, including: o Large sample size; o Multiple organisations; o Data across 10 years; and o Various indicators of health, including both mental and physical health are captured. Several limitations of this study need to also be acknowledged. These include: o Data were unable to be matched across time, thus interindividual change was not capture; o Health outcomes were measured inconsistently at times across years and organisations; o Intervention detail was lacking; o Work-related variable details were also lacking, for instance, work hours and management level. Recommendations Recommendation to improve data collection and integration Data consistency was a main challenge of this project. Our initial investigation found the data formats varied between organisations and sometimes within the same company. For example, an excel dataset with multiple data format for the same data or alphanumeric data stored in a numeric field. This could be due to the way the data grew over the years, or reflect an absence of a data entry validation process, or the process of extracting the datasets. Data integration is concerned about combining data from multiple sources to minimize errors and provide data consistency. The following recommendation provides only a high level architecture; future analysis is required to investigate the level of integration of technology, people and processes within and between WHAA members. 22

31 High Level Architecture There are a number of stages required to data integration, starting from the initial stage of data extraction to the reporting stage. The high level architecture (Figure 7) provides a high level design for developing multi-layer framework for data integration. Figure 7 High Level Architecture 1. Datasets Datasets are a collection of (i) internal data such as demographic data, biometric data, (ii) external data such as specific health studies or research papers, and (iii) publically available data such as ABS datasets. All internal datasets were received from WHAA members. These datasets were inconsistent between the members and between external or publicly available datasets. The heterogeneity of such datasets requires a significant time to manipulate and cleanse before processing. ETL is a standard process to deal with multiple inconsistent datasets. 2. Extract, Transform and Load (ETL) Extract, Transform and Load (ETL) is the standard process that can be used in migrating diverse datasets into an optimized data warehouse environment. UOW receives data from a number of organisations in assorted file types provided in heterogeneous structures. These data are then extracted into a staging database where data cleaning, profiling and transforming operations take place. For example, detect incorrectly formatted records, removing or reporting inconsistent data fields, or removing unwanted data. Transformed data then loaded into a centralised star schema-based data warehouse. 3. Data warehouse The data warehouse can be based on a Star Schema design. It maps data into one or more fact tables with multidimensional tables. A star schema can simplify data structure and provide capability to analyse data from multiple dimensions. 23

32 4. Analytical reports The reports are built on top of the optimised star schema-based data warehouse. End users can access reports via an online portal with multiusers and multilevel access control. These access controls provide customised views of the data for different users. This recommended high level architecture provides high level of data integrity and validation. There are check points in each stage thereby allowing any issues to be reported before uploading to the data warehouse. The data warehouse provides flexibility in extracting and reporting data on a multiple levels. Recommendations for a core set of items for data collection: Recommendations for common core items to be included in HRA assessments can facilitate future research related to the impacts of HRA assessments and related feedback and counselling. It is also recommended that data on demographic and work-related variables such as country of birth, marital status, work hours and job type be included with the data in future collections. This approach should not be difficult to implement as these data are likely already available within organisations. Core items have been divided into essential and non-essential items. Detailed information is available in Appendix H. The recommended core items cover the following areas: Age/Date of birth Marital status Demographic variables (e.g. country of birth, language spoken at home) Education level (e.g. highest education level) Self-assessed health (e.g. Short-form Health Survey SF-12) Biometric variables (e.g. cholesterol, blood pressure) Health conditions (e.g. diabetes, heart condition) Health risk factors (e.g. alcohol consumption, physical activity) Organisational factors (e.g. job demands, work-family balance,) Organisational outcomes (e.g. presenteeism, absenteeism) Mental health (e.g. psychological distress, burnout) 24

33 Other recommendations It is also recommended that: Data are coded to allow matching over time, which also allows interindividual change to be captured. Intervention detail are included with the data. This can be achieved simply with a database of interventions each with a corresponding code which is entered next to the participant s data. Any interventions or health checks added over the years can then be included in the database and assigned a number. Demographic and job type details are included as per suggested core items. Research shows that demographic variables and job types can be potential antecedents to various health outcomes. Furthermore, studies suggest that individuals may be at greater risk based on demographic background. Including this information enables interventions to be tailored depending on need and there supports more effective and cost-efficient programs. Data integration methods are implemented as suggested to minimise errors and provide data consistency. Regular analysis and cleaning of data is conducted to reduce the enormity of the task compared to more occasional analysis. This approach also allows any errors to be rectified in a timely manner and for any edits to be made. Regular reporting and presenting of findings to the WHAA Board and its members. This approach offers the advantage of stimulating feedback and identify workplace health needs and issues in a timely manner, and providing greater accuracy and usefulness of data. 25

34 References ABS (Australian Bureau of Statistics) (2009). Long-term conditions. National Health Survey, Cat. No ABS (Australian Bureau of Statistics) (2011). Physical Activity in Australia: A Snapshot Cat. No ABS (Australian Bureau of Statistics) (2010). Psychological distress. Profiles of Health, Australia, Cat. No ABS (Australian Bureau of Statistics) (2013a). Cholesterol. Australian Health Survey: Biomedical Results for Chronic Diseases, Cat. no ABS (Australian Bureau of Statistics) (2013b). Profiles of Health, Australia, Cat no ABS (Australian Bureau of Statistics) (2013c). Overweight/obesity. Gender Indicators, Australia, Jan Cat. No AIHW (2012). Australia's health Australia's health no. 13. Cat. no. AUS 156. Canberra: AIHW. AIHW (2014). Australia s Health Australia s health series no. 14. Cat no. AUS 178. Canberra: Australian Institute of Health and Welfare. AIHW analysis of AusDiab study. Aldana, S. G., & Greenlaw, R. L. (2005). The effects of a worksite chronic disease prevention program. J Occup Environ Med, 47, Anderson, B. K., & Larimer, M. E. (2002). Problem drinking and the workplace: an individualised approach to prevention. Psychol Addict Behav, 16, Casey, L. (2013). Stress and Wellbeing in Australia Survey Australian Psychological Society Engbers, L. H., van Poppel, M. N. M., & van Mechelen, W. (2007). Modest effects of a controlled worksite environmental intervention on cardiovascular risk in office workers. Preventative Medicine, 44, Naito, M. T., & Nakayama, e. a. (2008). Effect of a 4-year workplace based physical activity intervention program on the blood lipid profiles of participating employees: the high-risk and population strategy for occupational health promotion (HIPOP-OHP) study. Atherosclerosis, 197, NHMRC (National Health and Medical Research Council) (2013). Australian Dietary Guidelines. Department of Health and Ageing: Canberra. Proper, K.I. and M. Koning, The effectiveness of worksite physical activity programs on physical activity, physical fitness, and health. Clin J Sport Med, : p Smedslund, G. and K.J. Fisher, The effectiveness of workplace smoking cessation programmes: a meta-analysis of recent studies. Tob Control, : p Smedslund, G., & Fisher, K. J. (2004). The effectiveness of workplace smoking cessation programmes: A meta-analysis of recent studies. Tob Control, 13, Tobacco smoking (NDSHS 2013 key findings) AIHW Whitworth, J.A. (2003). WHO, International Society of Hypertension Writing group Workplace Gender Equality Agency (2014). Gender Workplace Statistics at a Glance, 26

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36 APPENDIX A. DEFINITIONS Definitions Daily smoking High blood pressure (Hypertension) Weight Obesity Overweight High waist-hip ratio Cholesterol Total Smoking tobacco products daily A blood reassure reading when systolic or diastolic blood pressure is greater than or equal to 140/90mmHg A body mass index (BMI) of 30 or more A body mass index (BMI) of 25 to 30 In men, a ratio 1.0 or more, and in women, a ratio of 0.85 or more A total cholesterol reading greater than or equal to 5.5 mmol/l Impaired fasting glucose (IFG) Impaired Glucose Tolerance (IGT) Insufficient amounts of fruit Insufficient amounts of vegetables Physical inactivity Waist circumference Blood glucose level is higher than normal after fasting for 8 hours (between 6.1 & 6.9 mmol/l) but not high enough to diagnose diabetes Blood glucose level is between 7.8 & 11.0 mmol/l using an Oral Glucose Tolerance Test and the two hour blood test. Usual consumption of fewer than two serves of fruit per day Usual consumption of fewer than five serves of vegetables per day Not participating in the recommended minimum level of activity 150 minutes per week over at least 5 sessions. At risk is for men, a measure of 1.0 or more and for women, 0.85 or more. 28

37 APPENDIX B. SAMPLE CHARACTERISTICS AND A SNAPSHOT OF EMPLOYEE HEALTH Some descriptive characteristics for employees included in the analysis are provided below in Table B1. Table B1 Characteristics of the sample between 2010 and N* Age, mean (SD) Gender Male Female 41.0 (11.4) years 3199 (57.2%) 2372 (42.6%) 40.9 (11.3) years 4207 (57.1%) 3156 (42.9%) 41.4 (11.3) years 3076 (47.6%) 3390 (52.4%) 43.1 (11.1) years 3546 (51.4%) 3357 (48.6%) 41.3 (11.6) years 1281 (52.5%) 1159 (47.5%) State NSW ACT Tas QLD WA NT Overseas 95 (15.3%) 431 (69.4%) 7 (1.1%) 39 (6.3%) 41 (6.6%) 6 (1.0%) 2 (.3%) 110 (8.5%) 1005 (78.0%) 67 (5.2%) 26 (2.0%) 37 (2.9%) 38 (3.0%) 5 (.4%) 77 (5.5%) 934 (67.1%) 229 (16.5%) 20 (1.4%) 51 (3.7%) 76 (5.5%) 5 (.4%) 65 (11.5%) 445 (79.0%) 1 (.2%) 17 (3.0%) 18 (3.2%) 2 (.4%) 15 (2.7%) 36 (13.7%) 167 (63.7%) 7 (2.7%) 21 (8.0%) 31 (11.8%) 0 0 * Sample size varies throughout report due to missing data 29

38 A snapshot of employee health Age groups The majority of individuals sampled in 2013 were aged between 25 and 54 years (80.6%)(Figure B1) Figure B1. Age groups of individuals in

39 APPENDIX C. TRENDS IN HEALTH ( ) Biometric Health Outcomes High blood pressure/hypertension Definition: High blood pressure, also known as hypertension, is defined by WHO (Whitworth; 2003) as systolic blood pressure of 140mmHg or more diastolic blood pressure of 90mmHG or more receiving medication for high blood pressure. Data were collected on systolic and diastolic blood pressure but not on whether medication was being received. Therefore, for the purpose of this report, high blood pressure in employees will refer to those with either, or both, high systolic and diastolic blood pressure. Cholesterol Definition: Cholesterol is a fatty substance that is produced from saturated fats by the liver (AIHW, 2014). Insufficient physical activity and a diet high in saturated fats are risk factors for high cholesterol. Heart disease and strokes are a major risk associated with high cholesterol levels. A total cholesterol reading greater than 5.5 mmol/l is an indication of a greatly increased risk of developing coronary heart disease (AIHW, 2012). Cholesterol can be measured according to high density lipoprotein (HDL) and low density lipoprotein (LDL). In this report high cholesterol refers to the total cholesterol reading as this data was more consistently collected. We examined three measures of body composition: Body Mass Index (BMI), body fat percentage and waist circumference. Body Mass Index (BMI) Definition: BMI is calculated by dividing a person s weight (in kilograms) by their height (in metres) squared. BMI was used to categorised individuals into the following categories based on World Health Organization cut-offs: Category BMI Range Underweight < 18.5 kg/m 2 Healthy weight kg/m 2 Overweight kg/m 2 Obese 30 kg/m 2 31