Prevalence of osteoporosis in Australian men and women : Geelong osteoporosis study

To the Editor: Few reports have been published on bone mineral density (BMD) among randomly sampled populations. Organisations such as Osteoporosis Australia and the Australian and New Zealand Bone and Mineral Society rely on research to supply reliable data that are representative of the Australian community. This information informs practitioners, researchers and policymakers of the size of the problem of osteoporosis in Australia. Our study aimed to document the proportion of individuals who have reduced BMD.

Prevalence of osteoporosis in Australian women : Geelong Osteoporosis Study

To evaluate the prevalence of osteoporosis at various sites among Australian women, cross-sectional bone mineral density (BMD) data for adult females was obtained from an age-stratified population-based sample (n = 1494; 20–94 yr) drawn at random from the Barwon Statistical Division, a population characteristic of Australia. Age- and weight- (and for three sites, height) matched reference ranges for BMD at the lumbar spine, proximal femur, forearm, and total body were developed using regression techniques. The cutoff BMD level for osteoporosis at the PA spine was 0.917 g/cm² and 0.713 g/cm² at the femoral neck according to the World Health Organization (WHO) guidelines. The upper cutoff level for osteopenia was 1.128 g/cm² at the PA spine and 0.913 g/cm² for the femoral neck. The proportion of Australian women categorized as having osteoporosis at the PA spine, femoral neck, or midforearm ranged from 0.9% among those aged 40–44 yr to 87.0% for those older than 79 yr. This study provides reference data representative of the Australian female population. A large proportion of elderly Australian women has osteoporosis according to the WHO guidelines.

Prevalence of obesity and the relationship between the body mass index and body fat : cross-sectional, population-based data

Background: Anthropometric measures such as the body mass index (BMI) and waist circumference are widely used as convenient indices of adiposity, yet there are limitations in their estimates of body fat. We aimed to determine the prevalence of obesity using criteria based on the BMI and waist circumference, and to examine the relationship between the BMI and body fat.

Methodology/Principal Findings: This population-based, cross-sectional study was conducted as part of the Geelong Osteoporosis Study. A random sample of 1,467 men and 1,076 women aged 20–96 years was assessed 2001–2008. Overweight and obesity were identified according to BMI (overweight 25.0–29.9 kg/m2; obesity $30.0 kg/m2) and waist circumference (overweight men 94.0–101.9 cm; women 80.0–87.9 cm; obesity men $102.0 cm, women $88.0 cm); body fat mass was assessed using dual energy X-ray absorptiometry; height and weight were measured and lifestyle factors documented by self-report. According to the BMI, 45.1% (95%CI 42.4–47.9) of men and 30.2% (95%CI 27.4–33.0) of women were overweight and a further 20.2% (95%CI 18.0–22.4) of men and 28.6% (95%CI 25.8–31.3) of women were obese. Using waist circumference, 27.5% (95%CI 25.1–30.0) of men and 23.3% (95%CI 20.8–25.9) of women were overweight, and 29.3% (95%CI 26.9–31.7) of men and 44.1% (95%CI 41.2–47.1) of women, obese. Both criteria indicate that approximately 60% of the population exceeded recommended thresholds for healthy body habitus. There was no consistent pattern apparent between BMI and energy intake. Compared with women, BMI overestimated adiposity in men, whose excess weight was largely attributable to muscular body builds and greater bone mass. BMI also underestimated adiposity in the elderly. Regression models including gender, age and BMI explained 0.825 of the variance in percent body fat.

Conclusions/Significance: As the BMI does not account for differences in body composition, we suggest that gender- and age-specific thresholds should be considered when the BMI is used to indicate adiposity.

The exclusion of high trauma fractures may underestimate the prevalence of bone fragility fractures in the community : the Geelong Osteoporosis Study

Fractures associated with severe trauma are generally excluded from estimates of the prevalence of osteoporotic fractures in the community. Because the degree of trauma is difficult to quantitate, low bone mass may contribute to fractures following severe trauma. We ascertained all fractures in a defined population and compared the bone mineral density (BMD) of women who sustained fractures in either 'low' or 'high' trauma events with the BMD of a random sample of women from the same population. BMD was measured by dual-energy X-ray absorptiometry and expressed as a standardized deviation (Z score) adjusted for age. The BMD Z scores (mean ± SEM) were reduced in both the low and high trauma groups, respectively: spine-posterior-anterior (- 0.50 ± 0.05 and -0.21 ± 0.08), spine-lateral (-0.28 ± 0.06 and -0.19 ± 0.10), femoral neck (-0.42 ± 0.04 and -0.26 ± 0.09), Ward's triangle (- 0.44 ± 0.04 and -0.28 ± 0.08), trochanter (-0.44 ± 0.05 and -0.32 ± 0.08), total body (-0.46 ± 0.06 and -0.32 ± 0.08), ultradistal radius (- 0.47 ± 0.05 and -0.42 ± 0.07), and midradius (-0.52 ± 0.06 and -0.33 ± 0.09). Except at the PA spine, the deficits were no smaller in the high trauma group. Compared with the population, the age-adjusted odds ratio for osteoporosis (t-score < -2.5) at one or more scanning sites was 3.1 (95% confidence interval 1.9, 5.0) in the high trauma group and 2.7 (1.9, 3.8) in the low trauma group. The data suggest that the exclusion of high trauma fractures in women over 50 years of age may result in underestimation of the contribution of osteoporosis to fractures in the community. Bone density measurement of women over 50 years of age who sustain fractures may be warranted irrespective of the classification of trauma.

The high prevalence of vitamin D insufficiency across Australian populations is only partly explained by season and latitude

Background Inadequate sun exposure and dietary vitamin D intake can result in vitamin D insufficiency. However, limited data are available on actual vitamin D status and predictors in healthy individuals in different regions and by season.

Methods We compared vitamin D status [25-hydroxyvitamin D; 25(OH)D] in people < 60 years of age using data from cross-sectional studies of three regions across Australia: southeast Queensland (27°S; 167 females and 211 males), Geelong region (38°S; 561 females), and Tasmania (43°S; 432 females and 298 males).

Results The prevalence of vitamin D insufficiency (≤ 50 nmol/L) in women in winter/spring was 40.5% in southeast Queensland, 37.4% in the Geelong region, and 67.3% in Tasmania. Season, simulated maximum daily duration of vitamin D synthesis, and vitamin D effective daily dose each explained around 14% of the variation in 25(OH)D. Although latitude explained only 3.9% of the variation, a decrease in average 25(OH)D of 1.0 (95% confidence interval, 0.7–1.3) nmol/L for every degree increase in latitude may be clinically relevant. In some months, we found a high insufficiency or even deficiency when sun exposure protection would be recommended on the basis of the simulated ultraviolet index.

Conclusion Vitamin D insufficiency is common over a wide latitude range in Australia. Season appears to be more important than latitude, but both accounted for less than one-fifth of the variation in serum 25(OH)D levels, highlighting the importance of behavioral factors. Current sun exposure guidelines do not seem to fully prevent vitamin D insufficiency, and consideration should be given to their modification or to pursuing other means to achieve vitamin D adequacy.

A review of population-based prevalence studies of physical activity in adults in the Asia-Pacific region

Background: Physical activity (PA) surveillance is an important component of non-communicable disease risk factor monitoring, and occurs through national and international surveillance systems. This review identifies population PA estimates for adults in the Asia-Pacific region, and examines variation in trends and prevalence rates obtained using different PA measures.

Methods: Data were obtained from a MEDLINE search; World Health Organization’s Global Health Infobase; Government websites and reference lists of relevant papers. Inclusion criteria included: national studies or those reporting large scale population-level data; data published from 2000 to 2010 and trend data prior; sample sizes over n = 1000, or fewer subjects in small nations.

Results: In total, 56 population surveys from 29 Asia-Pacific countries were identified. Data on ‘sufficient physical activity’ amongst adults were available from 45 studies (80%), with estimates ranging from 7% to 93% (median 62%, inter-quartile range 40%-85%). For 14 countries, estimates of ‘sufficient activity’ were documented in multiple surveys using different methods, with the largest variation from 18% to 92% in Nepal. Median or mean METminutes/ day, reported in 20 studies, ranged from 6 to 1356. Serial trend data were available for 11 countries (22%), for periods spanning 2-10 years. Of these, five countries demonstrated increases in physical activity over time, four demonstrated decreases and three showed no changes.

Conclusions: Many countries in the Asia-Pacific region collect population-level PA data. This review highlights differences in estimates within and between countries. Some differences may be real, others due to variation in the PA questions asked and survey methods used. Use of standardized protocols and measures, and combined reporting of data are essential goals of improved international PA surveillance.

Prevalence of vitamin D deficiency and its determinants in Australian adults aged 25 years and older : a national, population-based study

Objective  Vitamin D deficiency is recognized as a global public health problem, but the population-based prevalence of deficiency and its determinants in Australian adults is not known. This study evaluated the vitamin D status of Australian adults aged ≥25 years and risk factors associated with vitamin D deficiency in this population.

Design and Patients  We studied a national sample of 11 247 Australian adults enrolled in the 1999/2000 Australian Diabetes, Obesity and Lifestyle (AusDiab) study drawn from 42 randomly selected districts throughout Australia.

Measurements  Serum concentrations of 25-hydroxyvitamin D [25(OH)D] were measured by immunoassay. Vitamin D deficiency was defined as a concentration <50 nmol/l. Information on demographic and lifestyle factors was derived from interview-administered questionnaires.

Results  The mean serum 25(OH)D concentration was 63 nmol/l (95% CI: 59–67 nmol/l). Only 4% of the population had a level <25 nmol/l, but the prevalence of vitamin D deficiency (<50 nmol/l) was 31% (22% men; 39% women); 73% had levels <75 nmol/l. The prevalence of vitamin D deficiency increased significantly with age, was greater in women, in those of non-Europid origin, in the obese and those who were physically inactive and with a higher level of education. Deficiency was also more common during winter and in people residing in southern Australia (latitude >35°S); 42% of women and 27% of men were deficient during summer–autumn, which increased to 58% and 35%, respectively, during winter–spring.

Conclusion  Vitamin D deficiency is common in Australia affecting nearly one-third of adults aged ≥25 years. This indicates that strategies are needed at the population level to improve vitamin D status of Australians.

Projected socioeconomic disparities in the prevalence of obesity among Australian adults

Objective: To project prevalence of normal weight, overweight and obesity by educational attainment, assuming a continuation of the observed individual weight change in the 5-year follow-up of the national population survey, the Australian Diabetes, Obesity and Lifestyle study (AusDiab; 2000–2005).

Methods: Age-specific transition probabilities between BMI categories, estimated using logistic regression, were entered into education-level-specific, incidence-based, multi-state life tables. Assuming a continuation of the weight change observed in AusDiab, these life tables estimate the prevalence of normal weight, overweight and obesity for Australian adults with low (secondary), medium (diploma) and high (degree) levels of education between 2005 and 2025.

Results: The prevalence of obesity among individuals with secondary level educational attainment is estimated to increase from 23% in 2000 to 44% in 2025. Among individuals with a degree qualification or higher, it will increase from 14% to 30%. If all current educational inequalities in weight change could be eliminated, the projected difference in the prevalence of obesity by 2025 between the highest and lowest educated categories would only be reduced by half (to a 6 percentage point difference from 14 percentage points).

Conclusion: We predict that almost half of Australian adults with low educational status will be obese by 2025. Current trends in obesity have the potential to drive an increase in the absolute difference in obesity prevalence between educational categories in future years.

Implications: Unless obesity prevention and management strategies focus specifically on narrowing social inequalities in obesity, inequalities in health are likely to widen.

Self-reported medication side effects in an older cohort living independently in the community - the Melbourne Longitudinal Study on Health Ageing (MELSHA) : cross-sectional analysis of prevalence and risk factors

Background Medication side effects are an important cause of morbidity, mortality and costs in older people. The aim of our study was to examine prevalence and risk factors for self-reported medication side effects in an older cohort living independently in the community.

Methods The Melbourne Longitudinal Study on Healthy Ageing (MELSHA), collected information on those aged 65 years or older living independently in the community and commenced in 1994. Data on medication side effects was collected from the baseline cohort (n = 1000) in face-to-face baseline interviews in 1994 and analysed as cross-sectional data. Risk factors examined were: socio-demographics, health status and medical conditions; medication use and health service factors. Analysis included univariate logistic regression to estimate unadjusted risk and multivariate logistic regression analysis to assess confounding and estimate adjusted risk.

Results Self-reported medication side effects were reported by approximately 6.7% (67/1000) of the entire baseline MELSHA cohort, and by 8.5% (65/761) of those on medication. Identified risk factors were increased education level, co-morbidities and health service factors including recency of visiting the pharmacist, attending younger doctors, and their doctor's awareness of their medications. The greatest increase in risk for medication side effects was associated with liver problems and their doctor's awareness of their medications. Aging and gender were not risk factors.

Conclusion Prevalence of self-reported medication side effects was comparable with that reported in adults attending General Practices in a primary care setting in Australia. The prevalence and identified risk factors provide further insight and opportunity to develop strategies to address the problem of medication side effects in older people living independently in the community setting.