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Abstract Background Multimorbidity, the simultaneous occurrence of two or more chronic conditions, is usually associated with older persons. This research assessed multimorbidity across a range of ages so that planners are informed and appropriate prevention programs, management strategies and health service/health care planning can be implemented. Methods Multimorbidity was assessed across three age groups from data collected in a major biomedical cohort study (North West Adelaide Health Study). Using randomly selected adults, diabetes, asthma, and chronic obstructive pulmonary disease were determined clinically and cardio-vascular disease, osteoporosis, arthritis and mental health by self-report (ever been told by a doctor). A range of demographic, social, risk and protective factors including high blood pressure and high cholesterol (assessed bio-medically), health service use, quality of life and medication use (linked to government records) were included in the multivariate modelling. Results Overall 4.4% of the 20-39 year age group, 15.0% of the 40-59 age group and 39.2% of those aged 60 years of age or older had multimorbidity (17.1% of the total). Of those with multimorbidity, 42.1% were aged less than 60 years of age. A variety of variables were included in the final logistic regression models for the three age groups including family structure, marital status, education attainment, country of birth, smoking status, obesity measurements, medication use, health service utilisation and overall health status. Conclusions Multimorbidity is not just associated with older persons and flexible care management support systems, appropriate guidelines and care-coordination programs are required across a broader age range. Issues such as health literacy and polypharamacy are also important considerations. Future research is required into assessing multimorbidity across the life course, prevention of complications and assessment of appropriate self-care strategies.

Abstract Background There is limited information on sleep duration and obesity among Australian children. The objective of the study is to cross-sectionally examine the relationship between sleep duration and obesity in Australian children aged 5 to 15 years. Methods Data were collected using the South Australian Monitoring and Surveillance System between January 2004 and December 2008. Each month a representative random sample of South Australians are selected from the Electronic White Pages with interviews conducted using Computer Assisted Telephone Interviewing (CATI). Within each household, the person who was last to have a birthday was selected for interview. Parents reported the number of hours their children slept each day. Obesity was defined according to the International Obesity Task Force (IOTF) definition based on BMI calculated from reported body weight and height. Results Overall, parents of 3495 children aged 5-15 years (mean 10.7 years, 50.3% boys) were interviewed. The prevalence of obesity was 7.7% (8.9% in boys, 6.6% in girls). In multivariate analysis after adjusting for sociodemographic variables, intake of fruit and vegetables, physical activity and inactivity, the odds ratio (OR) for obesity comparing sleeping Conclusion Short sleep duration is associated with increased obesity in children especially among younger age groups and boys.

Abstract Background Analysis was undertaken on data from randomly selected participants of a bio-medical cohort study to assess representativeness. The research hypotheses was that there was no difference in participation and non-participations in terms of health-related indicators (smoking, alcohol use, body mass index, physical activity, blood pressure and cholesterol readings and overall health status) and selected socio-demographics (age, sex, area of residence, education level, marital status and work status). Methods Randomly selected adults were recruited into a bio-medical representative cohort study based in the north western suburbs of the capital of South Australia – Adealide. Comparison data was obtained from cross-sectional surveys of randomly selected adults in the same age range and in the same region. The cohort participants were 4060 randomly selected adults (18+ years). Results There were no major differences between study participants and the comparison population in terms of current smoking status, body mass index, physical activity, overall health status and proportions with current high blood pressure and cholesterol readings. Significantly more people who reported a medium to very high alcohol risk participated in the study. There were some demographic differences with study participants more likely to be in the middle level of household income and education level. Conclusion People with risky behaviours participated in this health study in the same proportions as people without these risk factors.

Background: Individual-level health outcomes are shaped by environmental risk conditions. Norms figure prominently in socio-behavioural theories yet spatial variations in health-related norms have rarely been investigated as environmental risk conditions. This study assessed: 1) the contributions of local descriptive norms for overweight/obesity and dietary behaviour to 10-year change in glycosylated haemoglobin (HbA1c), accounting for food resource availability; and 2) whether associations between local descriptive norms and HbA1c were moderated by food resource availability.Methods: HbA1c, representing cardiometabolic risk, was measured three times over 10 years for a population-based biomedical cohort of adults in Adelaide, South Australia. Residential environmental exposures were defined using 1600 m participant-centred road-network buffers. Local descriptive norms for overweight/obesity and insufficient fruit intake (proportion of residents with BMI ≥ 25 kg/m2 [n = 1890] or fruit intake of <2 serves/day [n = 1945], respectively) were aggregated from responses to a separate geocoded population survey. Fast-food and healthful food resource availability (counts) were extracted from a retail database. Separate sets of multilevel models included different predictors, one local descriptive norm and either fast-food or healthful food resource availability, with area-level education and individual-level covariates (age, sex, employment status, education, marital status, and smoking status). Interactions between local descriptive norms and food resource availability were tested.Results: HbA1c concentration rose over time. Local descriptive norms for overweight/obesity and insufficient fruit intake predicted greater rates of increase in HbA1c. Neither fast-food nor healthful food resource availability were associated with change in HbA1c. Greater healthful food resource availability reduced the rate of increase in HbA1c concentration attributed to the overweight/obesity norm.Conclusions: Local descriptive health-related norms, not food resource availability, predicted 10-year change in HbA1c. Null findings for food resource availability may reflect a sufficiency or minimum threshold level of resources such that availability poses no barrier to obtaining healthful or unhealthful foods for this region. However, the influence of local descriptive norms varied according to food resource availability in effects on HbA1c. Local descriptive health-related norms have received little attention thus far but are important influences on individual cardiometabolic risk. Further research is needed to explore how local descriptive norms contribute to chronic disease risk and outcomes. [ABSTRACT FROM AUTHOR]

Background: Levels of vitamin D in the population have come under increasing scrutiny, however there are only a few studies in Australia which measure levels in the general population. The aim of this study was to measure the levels of vitamin D within a large population cohort and examine the association with seasons and selected demographic and health risk factors. Methods: A longitudinal cohort study of 2413 participants in the northwest suburbs of Adelaide, South Australia conducted between 2008 and 2010 was used to examine serum levels of 25-hydroxy vitamin D (25(OH)D) in relation to demographic characteristics (age, sex, income, education and country of birth), seasons, the use of vitamin D supplements and selected health risk factors (physical activity, body mass index and smoking). Both unadjusted and adjusted mean levels of serum 25(OH)D were examined, as were the factors associated with the unadjusted and adjusted prevalence of serum 25(OH)D levels below 50 and 75 nmol/L. Results: Overall, the mean level of serum 25(OH)D was 69.2 nmol/L with 22.7% of the population having a serum 25(OH)D level below 50 nmol/L, the level which is generally recognised as vitamin D deficiency. There were significantly higher levels of 25(OH)D among males compared to females (t = 4.65, p < 0.001). Higher levels of 25 (OH)D were also measured in summer and autumn compared with winter and spring. Generally, mean levels of 25 (OH)D were lower in those classified as obese. Smokers and those undertaking no or less than 150 minutes/week of physical activity also had lower levels of serum vitamin D. Obesity (as classified by body mass index), season and undertaking an insufficient level of physical activity to obtain a health benefit were significantly associated with the prevalence of vitamin D deficiency. Conclusions: Vitamin D deficiency is prevalent in South Australia, affecting almost one quarter of the population and levels are related to activity, obesity and season even when adjusted for confounding factors. Improved methods of addressing vitamin D levels in population are required. [ABSTRACT FROM AUTHOR]

Background: The evidence linking socioeconomic environments and metabolic syndrome (MetS) has primarily been based on cross-sectional studies. This study prospectively examined the relationships between area-level socioeconomic position (SEP) and the incidence of MetS. Methods: A prospective cohort study design was employed involving 1,877 men and women aged 18+ living in metropolitan Adelaide, Australia, all free of MetS at baseline. Area-level SEP measures, derived from Census data, included proportion of residents completing a university education, and median household weekly income. MetS, defined according to International Diabetes Federation, was ascertained after an average of 3.6 years follow up. Associations between each area-level SEP measure and incident MetS were examined by Poisson regression Generalised Estimating Equations models. Interaction between area- and individual-level SEP variables was also tested. Results: A total of 156 men (18.7%) and 153 women (13.1%) developed MetS. Each percentage increase in the proportion of residents with a university education corresponded to a 2% lower risk of developing MetS (age and sex-adjusted incidence risk ratio (RR) = 0.98; 95% confidence interval (CI) =0.97-0.99). This association persisted after adjustment for individual-level income, education, and health behaviours. There was no significant association between area-level income and incident MetS overall. For the high income participants, however, a one standard deviation increase in median household weekly income was associated with a 29% higher risk of developing MetS (Adjusted RR = 1.29; 95%CI = 1.04-1.60). Conclusions: While area-level education was independently and inversely associated with the risk of developing MetS, the association between area-level income and the MetS incidence was modified by individual-level income. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity, the simultaneous occurrence of two or more chronic conditions, is usually associated with older persons. This research assessed multimorbidity across a range of ages so that planners are informed and appropriate prevention programs, management strategies and health service/health care planning can be implemented. Methods: Multimorbidity was assessed across three age groups from data collected in a major biomedical cohort study (North West Adelaide Health Study). Using randomly selected adults, diabetes, asthma, and chronic obstructive pulmonary disease were determined clinically and cardio-vascular disease, osteoporosis, arthritis and mental health by self-report (ever been told by a doctor). A range of demographic, social, risk and protective factors including high blood pressure and high cholesterol (assessed bio-medically), health service use, quality of life and medication use (linked to government records) were included in the multivariate modelling. Results: Overall 4.4% of the 20-39 year age group, 15.0% of the 40-59 age group and 39.2% of those aged 60 years of age or older had multimorbidity (17.1% of the total). Of those with multimorbidity, 42.1% were aged less than 60 years of age. A variety of variables were included in the final logistic regression models for the three age groups including family structure, marital status, education attainment, country of birth, smoking status, obesity measurements, medication use, health service utilisation and overall health status. Conclusions: Multimorbidity is not just associated with older persons and flexible care management support systems, appropriate guidelines and care-coordination programs are required across a broader age range. Issues such as health literacy and polypharamacy are also important considerations. Future research is required into assessing multimorbidity across the life course, prevention of complications and assessment of appropriate self-care strategies. [ABSTRACT FROM AUTHOR]

Background: There is limited information on sleep duration and obesity among Australian children. The objective of the study is to cross-sectionally examine the relationship between sleep duration and obesity in Australian children aged 5 to 15 years. Methods: Data were collected using the South Australian Monitoring and Surveillance System between January 2004 and December 2008. Each month a representative random sample of South Australians are selected from the Electronic White Pages with interviews conducted using Computer Assisted Telephone Interviewing (CATI). Within each household, the person who was last to have a birthday was selected for interview. Parents reported the number of hours their children slept each day. Obesity was defined according to the International Obesity Task Force (IOTF) definition based on BMI calculated from reported body weight and height. Results: Overall, parents of 3495 children aged 5-15 years (mean 10.7 years, 50.3% boys) were interviewed. The prevalence of obesity was 7.7% (8.9% in boys, 6.6% in girls). In multivariate analysis after adjusting for sociodemographic variables, intake of fruit and vegetables, physical activity and inactivity, the odds ratio (OR) for obesity comparing sleeping <9 hours with ≥10 hours was 2.23 (95% CI 1.04-4.76) among boys, 1.70(0.78-3.73) among girls, and 1.97(1.15-3.38) in both genders. The association between short sleep (<9 hours) and obesity was stronger in the younger age group. No significant association between short sleep and obesity was found among children aged 13-15. There was also an additive interaction between short sleep and low level of physical activity. Conclusion: Short sleep duration is associated with increased obesity in children especially among younger age groups and boys. [ABSTRACT FROM AUTHOR]

Background: Analysis was undertaken on data from randomly selected participants of a biomedical cohort study to assess representativeness. The research hypotheses was that there was no difference in participation and non-participations in terms of health-related indicators (smoking, alcohol use, body mass index, physical activity, blood pressure and cholesterol readings and overall health status) and selected socio-demographics (age, sex, area of residence, education level, marital status and work status). Methods: Randomly selected adults were recruited into a bio-medical representative cohort study based in the north western suburbs of the capital of South Australia -- Adelaide. Comparison data was obtained from cross-sectional surveys of randomly selected adults in the same age range and in the same region. The cohort participants were 4060 randomly selected adults (18+ years). Results: There were no major differences between study participants and the comparison population in terms of current smoking status, body mass index, physical activity, overall health status and proportions with current high blood pressure and cholesterol readings. Significantly more people who reported a medium to very high alcohol risk participated in the study. There were some demographic differences with study participants more likely to be in the middle level of household income and education level. Conclusion: People with risky behaviours participated in this health study in the same proportions as people without these risk factors. [ABSTRACT FROM AUTHOR]