North West Adelaide Health Study Research Articles

Pregnancy Complications Are Associated with Premature Coronary Artery Disease: Linking Three Cohorts.

Background: There is increasing evidence that women who experience placenta-mediated pregnancy complications and gestational diabetes mellitus (GDM) are at higher risk for the development of coronary artery disease (CAD) later in life. We hypothesized that there is an association between placenta-mediated pregnancy complications, GDM, and risk of premature CAD (PCAD). Methods: This research project involved a data linkage approach merging three databases of South Australian cohorts by using a retrospective, age-matched case-control study design. Cases (n = 721) were ascertained from the Coronary Angiogram Database of South Australia (CADOSA). Women <60 years from CADOSA were linked to South Australian Perinatal Statistics Collection (SAPSC) to ascertain their prior pregnancy outcomes. Controls (n = 194) were selected from North West Adelaide Health Study (NWAHS) and comprised women who were healthy or had other health conditions unrelated to CAD, age-matched to CADOSA (±5 years), and linked to SAPSC to determine their pregnancy outcomes. PCAD was defined as >50% stenosis in one or more coronary arteries at coronary angiography. Results: Compared with women without a history of PCAD, women who were diagnosed with PCAD were more likely to have experienced the placenta-mediated pregnancy complications of preterm birth (adjusted odds ratio [OR] = 2.46, 95% confidence interval [CI]: 1.21-5.00) or low-birth weight (adjusted OR = 2.44, 95% CI: 1.22-4.88), or have been diagnosed with active asthma during pregnancy (adjusted OR = 3.52, 95% CI: 1.05-11.76). Conclusion: Placenta-mediated pregnancy complications should be recognized as clear risk markers for future PCAD.

Abstract 10005: Pregnancy Complications Are Associated With Premature Coronary Artery Disease - Linking Three South Australian Cohorts

Introduction: There is increasing evidence that women who experience placenta-mediated pregnancy complications and gestational diabetes mellitus (GDM) are more likely to develop coronary artery disease (CAD) at a younger age. This is the first study to assess the relationship between pregnancy complications and premature coronary artery disease (PCAD) in Australian women. Hypothesis: We hypothesized that there is an association between placenta-mediated pregnancy complications, GDM and risk of CAD prior to 60 years of age. Methods: The research project involved a data linkage approach merging three databases of South Australian cohorts by employing a retrospective, age-matched case-control study design. Cases (n=721) were ascertained from Coronary Angiogram Database of South Australia (CADOSA). Women &lt;60 years from CADOSA were linked to South Australian Perinatal Statistics Collection (SAPSC) to determine their pregnancy outcomes. Controls (n=194) were ascertained from North West Adelaide Health Study (NWAHS) and comprised of women who were healthy or had health conditions other than CAD, age-matched to CADOSA (+/- 5 years) and linked to SAPSC to determine their pregnancy outcomes. PCAD was defined as &gt; 50% stenosis in one or more coronary arteries at coronary angiography. Results: Women who were diagnosed with PCAD were more likely to have experienced a placenta-mediated pregnancy complication, previous miscarriage, asthma or anaemia and/or have risk factors for CAD including pre-existing diabetes (I &amp; II), active smoking and obesity during pregnancy compared to women without a history of CAD as shown in the table below (p &lt; 0.05). GDM was not associated with PCAD in these cohorts. Conclusion: Women diagnosed with PCAD have conventional CVD risk factors and some that are uniquely related to their pregnancy. These clinical events may be considered novel risk factors for future PCAD and require attention in contemporary preventative cardiology practice.

Association of dietary and nutrient patterns with systemic inflammation in community dwelling adults

PurposeEvidence investigating associations between dietary and nutrient patterns and inflammatory biomarkers is inconsistent and scarce. Therefore, we aimed to determine the association of dietary and nutrient patterns with inflammation.MethodsOverall, 1,792 participants from the North-West Adelaide Health Study were included in this cross-sectional study. We derived dietary and nutrient patterns from food frequency questionnaire data using principal component analysis. Multivariable ordinal logistic regression determined the association between dietary and nutrient patterns and the grade of inflammation (normal, moderate, and severe) based on C-reactive protein (CRP) values. Subgroup analyses were stratified by gender, obesity and metabolic health status.ResultsIn the fully adjusted model, a plant-sourced nutrient pattern (NP) was strongly associated with a lower grade of inflammation in men (ORQ5vsQ1 = 0.59, 95% CI: 0.38–0.93, p-trend = 0.08), obesity (ORQ5vsQ1 = 0.43; 95% CI: 0.24–0.77, p-trend = 0.03) and metabolically unhealthy obesity (ORQ5vsQ1 = 0.24; 95% CI: 0.11–0.52, p-trend = 0.01). A mixed NP was positively associated with higher grade of inflammation (ORQ5vsQ1 = 1.35; 95% CI: 0.99–1.84, p-trend = 0.03) in all participants. A prudent dietary pattern was inversely associated with a lower grade of inflammation (ORQ5vsQ1 = 0.72, 95% CI: 0.52–1.01, p-trend = 0.14). In contrast, a western dietary pattern and animal-sourced NP were associated with a higher grade of inflammation in the all participants although BMI attenuated the magnitude of association (ORQ5vsQ1 = 0.83, 95% CI: 0.55–1.25; and ORQ5vsQ1 = 0.94, 95% CI: 0.63–1.39, respectively) in the fully adjusted model.ConclusionA plant-sourced NP was independently associated with lower inflammation. The association was stronger in men, and those classified as obese and metabolically unhealthy obese. Increasing consumption of plant-based foods may mitigate obesity-induced inflammation and its consequences.

880Dietary inflammatory index and the risk of adult depression symptoms

Abstract Background The link between diet, inflammation and depressive symptoms (DepS) are of increasing interest. The study aims to assess the association between the dietary inflammatory index (DII®) and DepS using the North-West Adelaide Health Study (NWAHS) cohort and update the previous meta-analysis. Methods A total of 1743 (mean□SD age 56.6±13.6 years, 51% female) and 859 (mean□SD age 58.4±12.1 years, 52.6% female) of NWAHS participants were included for cross-sectional and longitudinal analysis respectively. DII was determined using food frequency questionnaires, and the Center for Epidemiologic Studies Depression Scale (CES-D) assessed DepS. Log- and negative binomial regression were used to assess the association between quartiles of DII and DepS. Results In a fully adjusted model, higher DII score (i.e. pro-inflammatory diet) was associated with 79% increase in odds of reporting DepS (ORQuartile4vs1:1.79; 95% CI: 1.14-2.81; ptrend=0.026). Men with higher DII had two-fold higher odds of DepS (ORQuartile4vs1:2.27; 95% CI: 1.02-5.06; ptrend=0.089). Women with higher DII had an 81% increase in odds of DepS (ORQuartile4vs1:1.81; 95% CI: 1.01-3.26; ptrend=0.068). These associations were consistent in the longitudinal analysis. The meta-analysis (n = 12) showed that a pro-inflammatory diet was associated with a 45% increase in odds of having DepS (ORQuartile4vs1:1.45; 95% CI: 1.20,1.74, p-value&amp;lt;0.01). Conclusions A pro-inflammatory diet was positively associated with increased risk of DepS. Our findings support the current evidence that shows the role of pro-inflammatory diet in DepS. Key messages Increase the consumption of anti-inflammatory diet to reduce depressive symptoms

Association between Dietary Inflammatory Index, Dietary Patterns, Plant-Based Dietary Index and the Risk of Obesity.

Evidence on the association between various dietary constructs and obesity risk is limited. This study aims to investigate the longitudinal relationship between different diet indices and dietary patterns with the risk of obesity. Non-obese participants (n = 787) in the North West Adelaide Health Study were followed from 2010 to 2015. The dietary inflammatory index (DII®), plant-based dietary index (PDI) and factor-derived dietary pattern scores were computed based on food frequency questionnaire data. We found the incidence of obesity was 7.62% at the 5-year follow up. In the adjusted model, results from multivariable log-binomial logistic regression showed that a prudent dietary pattern (RRQ5 vs. Q1 = 0.38; 95% CI: 0.15–0.96), healthy PDI (RR = 0.31; 95% CI: 0.12–0.77) and overall PDI (RR = 0.56; 95% CI: 0.23–1.33) were inversely associated with obesity risk. Conversely, the DII (RR = 1.59; 95% CI: 0.72–3.50), a Western dietary pattern (RR = 2.16; 95% CI: 0.76–6.08) and unhealthy PDI (RR = 1.94; 95% CI: 0.81–4.66) were associated with increased risk of obesity. Based on the cubic spline analysis, the association between an unhealthy PDI or diet quality with the risk of obesity was non-linear. In conclusion, an anti-inflammatory diet, healthy diet or consumption of healthy plant-based foods were all associated with a lower risk of developing obesity.

Predicting Australian Adults at High Risk of Cardiovascular Disease Mortality Using Standard Risk Factors and Machine Learning.

Effective cardiovascular disease (CVD) prevention relies on timely identification and intervention for individuals at risk. Conventional formula-based techniques have been demonstrated to over- or under-predict the risk of CVD in the Australian population. This study assessed the ability of machine learning models to predict CVD mortality risk in the Australian population and compare performance with the well-established Framingham model. Data is drawn from three Australian cohort studies: the North West Adelaide Health Study (NWAHS), the Australian Diabetes, Obesity, and Lifestyle study, and the Melbourne Collaborative Cohort Study (MCCS). Four machine learning models for predicting 15-year CVD mortality risk were developed and compared to the 2008 Framingham model. Machine learning models performed significantly better compared to the Framingham model when applied to the three Australian cohorts. Machine learning based models improved prediction by 2.7% to 5.2% across three Australian cohorts. In an aggregated cohort, machine learning models improved prediction by up to 5.1% (area-under-curve (AUC) 0.852, 95% CI 0.837–0.867). Net reclassification improvement (NRI) was up to 26% with machine learning models. Machine learning based models also showed improved performance when stratified by sex and diabetes status. Results suggest a potential for improving CVD risk prediction in the Australian population using machine learning models.

Dietary inflammatory index (DII®) and the risk of depression symptoms in adults

Findings from observational studies investigating the association between Dietary Inflammatory Index (DII®) scores and depression symptoms (DepS) are inconsistent. This study aims to assess the association between energy-adjusted DII (E-DII™) and DepS using the North West Adelaide Health Study (NWAHS) cohort as well as update a previous meta-analysis. A total of 1743 (mean±SD age: 56.6±13.6 years, 51% female) study participants from NWAHS were included in the cross-sectional study and 859 (mean±SD age: 58.4±12.1 years, 52.6% female) in the longitudinal analyses. The Center for Epidemiological Studies Depression Scale (CES-D) was used for the measurement of DepS. E-DII scores were calculated from the dietary data collected using a validated food frequency questionnaire (FFQ). Data from two stages [Stage 3 (2008-10) and North West 15 (NW15) (2015)] were used. Log- and negative binomial regression were used to assess the association between quartiles of E-DII and DepS. A recent meta-analysis was updated by including 12 publications (six cross-sectional and six cohort studies) on the association between DII and DepS. In the cross-sectional analysis, a higher E-DII score (i.e., more pro-inflammatory diet) was associated with a 79% increase in odds of reporting DepS [ORQuartile4vs1: 1.79; 95% CI: 1.14-2.81; p=0.01; p for trend (ptrend)=0.03]. Males with higher E-DII had a more than two-fold higher odds of DepS (ORQuartile4vs1: 2.27; 95% CI: 1.02-5.06; p=0.045; ptrend=0.09). Females with higher E-DII had an 81% increase in odds of DepS (ORQuartile4vs1: 1.81; 95% CI: 1.01-3.26; p=0.046; ptrend=0.07). These associations were consistent in the longitudinal analysis. Comparing highest to lowest quintiles of E-DII, the updated meta-analysis showed that a pro-inflammatory diet is associated with a 45% increase in odds of having DepS (OR: 1.45; 95% CI: 1.20-1.74; p<0.01) with higher odds in females (OR: 1.53; 95% CI: 1.16-2.01; p=0.01) compared to their male counterparts (OR: 1.29; 95% CI: 0.98-1.69; p=0.15). The data from the NWAHS and the updated meta-analysis of observational studies provide further evidence that a pro-inflammatory diet is positively associated with increased risk of DepS. These findings support the current recommendation on consuming a less inflammatory diet to improve DepS.

Frailty and sarcopenia in combination are more predictive of mortality than either condition alone

BackgroundFrailty and sarcopenia are age-related conditions with shared features and are both associated with adverse health outcomes. Relatively little is known about outcomes of these conditions in combination. The aim of this study was to examine the predictive ability of combined frailty and sarcopenia classification on mortality. MethodsFrailty was measured in 716 community-dwelling adults aged ≥65 years from the North West Adelaide Health Study (mean age 74.1(6.1) years, 55.5 % female) using the frailty phenotype (FP) and sarcopenia using the revised consensus definition from the European Working Group on Sarcopenia. Participants were classified as: neither frail nor sarcopenic, frail-only, sarcopenic-only, or both frail and sarcopenic. All participants had a minimum of 10 years of mortality follow-up. ResultsWe identified 2.8 % of participants as both frail and sarcopenic, 15.5 % as frail-only, and 3.5 % as sarcopenic-only. Classification as both frail and sarcopenic, in a multivariable model, resulted in significantly elevated mortality risk (HR = 3.52, p < .001), which was over three times that of those neither frail nor sarcopenic. Frail-only was also a significant mortality predictor (HR = 2.03, p = .001), while classification as sarcopenic-only was not a significant predictor of mortality (HR = 1.65, p = .141). There was no significant difference in severity of frailty (mean number of characteristics) or grip strength between frail-only and those with both conditions when stratified by sex. ConclusionsIndividuals identified as frail would benefit from screening and assessment for sarcopenia, and vice versa for those identified as sarcopenic, as the mortality risk for individuals with these conditions in combination is nearly double that of each separately.

Association of metabolic phenotypes, grip strength and diabetes risk: The 15-year follow-up of The North West Adelaide Health Study, Australia

BackgroundThe association of diabetes risk in the long-term, metabolic phenotypes (MP) and muscle strength is unclear. We aimed to investigate the association between strictly defined MP, grip strength (GS) and diabetes. Material and methodsMP were defined according to BMI and presence of any individual metabolic abnormality for ≥18 years, in participants of the North West Adelaide Health Study (Australia) free of diabetes at baseline. The association of MP and dominant hand GS with incident diabetes over 15-years follow-up and the moderation effect of GS on the association between diabetes and MP were investigated by logistic regression models. ResultsOf 3039 participants followed over 13.3 years (SD 2.6), 236 (7.8%) developed diabetes. Compared to the metabolically healthy (MH) normal weight phenotype, the metabolically unhealthy (MU) overweight (OR 6.15, 95%CI 2.43–15.59) and obese (OR 12.32, 95%CI 4.97–30.52) phenotypes were associated with a high risk of diabetes, but not the MU normal weight (OR 1.73, 95%CI 0.57–5.25), MH overweight (OR 1.15, 95%CI 0.31–4.31) or MH obese phenotypes (OR 0.77, 0.07–8.89). GS was inversely associated with diabetes (OR 0.97, 95% CI 0.95–0.99) and attenuated the risk associated with MU overweight (beta = −0.296, p = 0.039) and MU normal weight (beta = −0.773; p for interaction = 0.009). ConclusionStrictly defined MP (rather than based on metabolic syndrome criteria) and GS, a proxy of muscle strength, might be useful for stratifying the risk of diabetes in the long-term. Improving muscle strength might be an important strategy to reduce diabetes risk.

Frailty state utility and minimally important difference: findings from the North West Adelaide Health Study.

frailty is a dynamic condition for which a range of interventions are available. Health state utilities are values that represent the strength of an individual's preference for specific health states, and are used in economic evaluation. This is a topic yet to be examined in detail for frailty. Likewise, little has been reported on minimally important difference (MID), the extent of change in frailty status that individuals consider to be important. to examine the relationship between frailty status, for both the frailty phenotype (FP) and frailty index (FI), and utility (preference-based health state), and to determine a MID for both frailty measures. population-based cohort of community-dwelling Australians. in total, 874 adults aged ≥65years (54% female), mean age 74.4 (6.2)years. frailty was measured using the FP and FI. Utilities were calculated using the short-form 6D health survey, with Australian and UK weighting applied. MID was calculated cross-sectionally. for both the FP and FI, frailty was significantly statistically associated (P< 0.001) with lower utility in an adjusted analysis using both Australian and UK weighting. Between-person MID for the FP was identified as 0.59 [standard deviation (SD) 0.31] (anchor-based) and 0.59 (distribution-based), whereas for the FI, MID was 0.11 (SD 0.05) (anchor-based) and 0.07 (distribution-based). frailty is significantly associated with lower preference-based health state utility. Frailty MID can be used to inform design of clinical trials and economic evaluations, as well as providing useful clinical information on frailty differences that patients consider important.

The Effect of Multimorbidity Patterns and the Impact of Comorbid Anxiety and Depression on Primary Health Service Use: The Men Androgen Inflammation Lifestyle Environment and Stress (MAILES) Study.

This study sought to determine patterns of multimorbidity and quantify their impact on use of primary health services in the presence and absence of anxiety and depression among a cohort of urban community-dwelling men in Australia. The analytic sample consisted of men (n = 2039; age 38–85) from the follow-up wave of a prospective cohort study of all participants of the Florey Adelaide Male Ageing Study (FAMAS; Stage 2 [2007–2010]) and age-matched men from the North-West Adelaide Health Study (NWAHS; Stage 3 [2008–2010]). Self-reported data and linkage with a national universal health coverage scheme (Medicare) provided information on the prevalence of eight chronic conditions and health service utilization information (including annual GP visits). Obesity and cardiovascular disease (CVD) were associated with the highest number of comorbid conditions. Two nonrandom multimorbidity “clusters” emerged: “CVD, Obesity, Diabetes” and “CVD, Obesity, Osteoarthritis.” Participants with conditions comorbid with CVD were more likely to have 10 or more annual GP visits, compared to multimorbidity involving other conditions. In comparison to participants without CVD, the presence of CVD increased the chance of having 10 or more annual GP visits (adjusted risk ratio: 3.7; 95% CI [2.8, 4.8]). When CVD was comorbid with anxiety and depression, having 10 or more annual GP visits was more common (adjusted risk ratio: 1.8; 95% CI [1.2, 2.5]). Multimorbidity patterns involving CVD, especially for multimorbidity that includes CVD with comorbid anxiety and depression, should be considered in developing clinical trials to better inform medical decision-making and care for patients with CVD and comorbid conditions.

Nutrient patterns and depressive symptoms among Australian adults.

Much of the current literature on the associations between diet and depression focus on single nutrients rather than nutrient patterns (NPs). We investigated the association between NPs and depressive symptoms (DepS) in an Australian adult population. DepS were examined at two different time points, in 2010 (Stage 3, n = 1743, 49.0% males) and 2015 [North West 2015 (NW15), n = 1,024, 46.6% males] of the North West Adelaide Health Study (NWAHS). Dietary habits were evaluated using a food frequency questionnaire (FFQ) at Stage 3. DepS were assessed using the Center for Epidemiological Studies Depression (CES-D) scale at Stage 3 and NW15. Principal component analysis was used to identify NPs as well as the factor structure of the CES-D. Log- and negative binomial regression analyses were used to assess the association between NPs and DepS scores. Ordinal logistic regression analysis was undertaken between the NPs and identified factors of the CES-D score. Three NPs (from theFFQ) and two-factors (from theCES-D score) were obtained. After adjusting for known confounding variables, a 'plant-sourced' NP (β-carotene, fibre, vitamin C, potassium and α-carotene) was inversely associated with DepS at Stage 3 [prevalence ratio (PR)Q4VsQ1, 0.78; 95% CI 0.66-0.92; p = 0.003], whereas an 'animal-sourced' (ω-3 fatty acid, monounsaturated fat, vitamin E and cholesterol) or 'mixed-source' (phosphorous, protein, vitamin B2, iodine and zinc) NP was not associated with DepS. There was an inverse relationship between the'plant-sourced' NP and the'(absence of) positive-affect' factor from the CES-D in both stages. The 'plant-sourced' NP is consistently and inversely associated with DepS; however, longitudinal studies are recommended to confirm these results.

Sleep Duration Moderates the Relationship Between Perceived Work-Life Interference and Depressive Symptoms in Australian Men and Women from the North West Adelaide Health Study.

Mental health disorders are prevalent and costly to workplaces and individuals in Australia. Work-life interference is thought to contribute negatively. The interplay between work-life interference, depressive symptoms and sleep has not been explored to date in population data. The aims of this study were to establish whether sleep duration moderates the relationship between work-life interference and depressive symptoms, and whether this is expressed differentially in male and female respondents. Data were drawn from the North West Adelaide Health Study (NWAHS) longitudinal, representative population-based cohort study. Working members of the cohort were invited to participate in a telephone survey about their work conditions, with an 86.7% response rate achieved. Data from 823 respondents were analysed after employing purposeful selection of covariates, using multivariable regression analysis. Sleep duration was found to moderate the relationship between work-life interference and depressive symptoms (F7,815= 26.60, p< 0.001), and accounted for 19% of the variance observed in depressive symptoms. The strongest effect of work-life interference on depressive symptoms was observed in habitual short sleepers, with the effect weakening as sleep duration increased. The relationship was observed in male and female respondents, but was stronger in females. Supporting and educating workers about the benefits of sleep for managing the relationship between work-life interference and depressive symptoms may offer a novel strategy for improving worker well-being, particularly when negative facets of work-life interference are not easily remedied or 'reduced'. There is a need for education and support strategies around sleep in Australian workplaces.

Association between dietary patterns and adult depression symptoms based on principal component analysis, reduced-rank regression and partial least-squares.

There have been inconsistent findings on the association between dietary patterns and depressive symptoms (DepS). In addition, studies have used single analysis methods to identify dietary patterns. In the current study, we aimed to determine the association between dietary patterns, derived by principal component analysis (PCA), reduced-rank regressions (RRR) and partial least-squares (PLS), and DepS among adults using a cohort study in Australia. We examined a total of 1743 study participants (≥24 years, 48.9% males) using cross-sectional and longitudinal data from the North West Adelaide Health Study (NWAHS). The Center for Epidemiological Studies-Depression (CES-D) scale was used to assess DepS and a score ≥16 was considered as having depression. Dietary data were collected using a food frequency questionnaire. Eicosapentaenoic acid (EPA)/Docosahexaenoic acid (DHA), folate, magnesium (Mg) and zinc (Zn) densities were chosen as the response variables for RRR and PLS analyses. Dietary patterns were identified by PCA, RRR and PLS. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated across quartiles (Q) using log-binomial logistic regression to assess the association between dietary patterns and DepS. Sensitivity analyses, including a longitudinal association between dietary patterns and DepS among 859 participants, were performed. Multiple imputation was performed to investigate the effect of missing data on the estimates. In this study, 16.9% (14.2% in men and 20.8% in women) of the participants had DepS. We retained two, four and four dietary patterns captured by PCA, RRR and PLS respectively. The 'prudent' pattern determined by PCA [ORQ4VsQ1=0.57; 95% CI: 0.35, 0.92] and PLS [ORQ4VsQ1=0.66; 95% CI: 0.43, 1.00] together with the 'typical Australian' pattern determined by RRR [ORQ4VsQ1=0.60; 95% CI: 0.40, 0.90] were inversely associated with DepS whereas the 'western' pattern derived by PCA [ORQ4VsQ1=2.04; 95% CI: 1.12, 3.68] and PLS [ORQ4VsQ1=1.62; 95% CI: 1.05, 2.50] was positively associated with DepS. In the longitudinal analysis, the 'prudent' pattern determined by PCA [ORQ4VsQ1=0.52; 95% CI: 0.25, 1.09] tended to be inversely associated with DepS whereas 'western' patterns determined by PCA [ORQ4VsQ1=3.47; 95% CI: 1.37, 8.78] and PLS [ORQ4VsQ1=2.47; 95% CI: 1.24, 4.91] were positively associated with DepS. We found that a dietary pattern characterized by high intakes of fruits, vegetables, medium fat dairy, nuts, legumes, and fish was inversely associated with DepS in this population-based study. Contrary to this, a dietary pattern characterized by high intakes of processed and red meat, fast foods (snacks and takeaway foods), soft drinks, white bread and high-fat dairy products were significantly associated with DepS. Multiple imputation and sensitivity analysis identified similar patterns of association between dietary pattern and DepS. The findings indicate that the 'western' pattern was consistently associated with an increased risk, and the 'prudent' pattern tended to be associated with a reduced risk of DepS. This suggests that dietary interventions may assist with the treatment of DepS. However, current evidence on the impact of diet on DepS should be supported using further longitudinal studies with extended follow up, larger sample sizes and repeated measures.

Association between Macronutrient Intake and Excessive Daytime Sleepiness: An Iso-Caloric Substitution Analysis from the North West Adelaide Health Study.

Epidemiological evidence on the association between macronutrient intake and excessive daytime sleepiness (EDS) is scarce. Using data from the North West Adelaide Health Study, we aimed to determine the association between iso-caloric substitution of macronutrients and EDS. Data from 1997 adults aged ≥ 24 years were analyzed. Daytime sleepiness was measured using the Epworth Sleepiness Scale, a score ≥ 11 was considered EDS. Dietary intake data were collected using a food frequency questionnaire. We determined absolute and relative energy intake based on consumption of saturated and unsaturated fats, protein, and carbohydrate. Odds ratios (ORs) were used to determine the associations using log-binomial logistic regression with and without iso-caloric substitution methods, and models were adjusted for confounders. The prevalence of EDS in the sample was 10.6%. After adjusting for potential confounders, substituting 5% energy intake from protein with an equal amount of saturated fat (OR = 1.57; 95% CI: 1.00–2.45) and carbohydrate (OR = 1.23; 95% CI: 0.92–1.65) increased the odds of EDS. When carbohydrate was substituted with saturated fat (OR = 1.27; 95% CI: 0.93–1.59), the odds of EDS were increased. The odds of EDS were lower when saturated fat was substituted with unsaturated fat (OR = 0.74; 95% CI: 0.51–1.06), protein (OR = 0.63; 95% CI: 0.41–0.99) or carbohydrate (OR = 0.79; 95% CI: 0.57–1.08). While these results were consistent over different iso-caloric substitution methods, inconsistent results were found with standard regression. While substitution of fat and carbohydrate with protein was inversely associated with EDS, substitution of protein with fat and carbohydrate was positively associated with EDS. Randomized trials are needed to confirm if dietary interventions can be used to improve daytime alertness in those with EDS.

Prevalence and healthcare usage of knee pain in South Australia: a population‐based study

It is known that South Australia (SA) has the highest rate of knee arthroscopy use of any state in Australia; however, Level 1 evidence demonstrates that knee arthroscopy in patients with uncomplicated knee osteoarthritis confers no benefit. In SA, which patients are presenting with knee pain and what treatments are they receiving? To determine the prevalence, persistence and treatment modalities of knee pain in SA. This study analysed data from the North-West Adelaide Health Study (1999-2015), a longitudinal, population-based cohort study of people aged 18 years and over (n = 4060), initially randomly selected from the north-west region of Adelaide, SA. It incorporated clinic assessments, self-completed questionnaires and telephone interviews to collect demographic, anthropometric and biochemical data over four main stages (1, 2, 3 and North-West 15 (NW15)). Data were linked to Medical Benefits Scheme data. In stages 3 and NW15 of the North-West Adelaide Health Study, 30-35% of participants reported knee pain (n = 803, 452). Demographic variables associated with knee pain included older age and lower educational level, while risk factors included obesity and high waist circumference. In the 12 months preceding NW15, 33% of participants with knee pain/stiffness consulted a general practitioner for their knee pain, 10.2% an orthopaedic surgeon, and 12.6% a physiotherapist. Between 2011 and 2015, 3.0% the cohort underwent a knee arthroscopy, and 3.1% underwent knee magnetic resonance imaging. Knee pain affects large proportions of the SA population. Knee pain was persistent with underuse of non-pharmacological treatments and high use of specialist referral. These data support the need for a national strategy to manage osteoarthritis effectively.

Sociodemographic, lifestyle and metabolic predictors of all-cause mortality in a cohort of community-dwelling population: an 18-year follow-up of the North West Adelaide Health Study

IntroductionStudies examining potential factors of all-cause mortality comprehensively at community level are rare. Using long-term community-based follow-up study, we examined the association of sociodemographic and behavioural characteristics, metabolic and chronic...

Recurrent Measurement of Frailty Is Important for Mortality Prediction: Findings from the North West Adelaide Health Study.

Frailty places individuals at greater risk of adverse health outcomes. However, it is a dynamic condition and may not always lead to decline. Our objective was to determine the relationship between frailty status (at baseline and follow-up) and mortality using both the frailty phenotype (FP) and frailty index (FI). Population-based cohort. Community-dwelling older adults. A total of 909 individuals aged 65 years or older (55% female), mean age 74.4 (SD 6.2) years, had frailty measurement at baseline. Overall, 549 participants had frailty measurement at two time points. Frailty was measured using the FP and FI, with a mean 4.5 years between baseline and follow-up. Mortality was matched to official death records with a minimum of 10 years of follow-up. For both measures, baseline frailty was a significant predictor of mortality up to 10 years, with initially good predictive ability (area under the curve [AUC] = .8-.9) decreasing over time. Repeated measurement at follow-up resulted in good prediction compared with lower (AUC = .6-.7) discrimination of equivalent baseline frailty status. In a multivariable model, frailty measurement at follow-up was a stronger predictor of mortality compared with baseline. Frailty change for the Continuous FI was a significant predictor of decreased or increased mortality risk based on corresponding improvement or worsening of score (hazard ratio = 1.04; 95% confidence interval = 1.02-1.07; P = .001). Frailty measurement is a good predictor of mortality up to 10 years; however, recency of frailty measurement is important for improved prediction. A regular review of frailty status is required in older adults. J Am Geriatr Soc 67:2311-2317, 2019.

Prevalence of Foot Pain Across an International Consortium of Population-Based Cohorts.

ObjectiveDespite the potential burden of foot pain, some of the most fundamental epidemiologic questions surrounding the foot remain poorly explored. The prevalence of foot pain has proven to be difficult to compare across existing studies due to variations in case definitions. The objective of this study was to investigate the prevalence of foot pain in several international population‐based cohorts using original data and to explore differences in the case definitions used.MethodsFoot pain variables were examined in 5 cohorts: the Chingford 1000 Women Study, the Johnston County Osteoarthritis Project, the Framingham Foot Study, the Clinical Assessment Study of the Foot, and the North West Adelaide Health Study. One question about foot pain was chosen from each cohort based on its similarity to the American College of Rheumatology pain question.ResultsThe precise definition of foot pain varied between the cohorts. The prevalence of foot pain ranged from 13% to 36% and was lowest in the cohort in which the case definition specific to pain was used, compared to the 4 remaining cohorts in which a definition included components of pain, aching, or stiffness. Foot pain was generally more prevalent in women and obese individuals and generally increased with age, with the prevalence being much lower in younger participants (ages 20–44 years).ConclusionFoot pain is common and is associated with female sex, older age, and obesity. Estimates of the prevalence of foot pain are likely to be affected by the case definition used. Therefore, in future population studies, the use of consistent measures of data collection must be considered.

Association of Statin Exposure With Histologically Confirmed Idiopathic Inflammatory Myositis in an Australian Population

Statin medications are widely prescribed for cardiovascular risk reduction. Myalgia and rhabdomyolysis are well-recognized adverse effects of statins, and they resolve with the cessation of statin therapy. Idiopathic inflammatory myositis (IIM) is a heterogeneous group of autoimmune myopathies that may also be associated with statin use. Recently, statin-associated autoimmune myopathy has been recognized as a distinct entity with the presence of specific autoantibodies against hydroxymethylglutaryl-coenzyme A reductase, which results in a necrotizing myositis that does not resolve with cessation of statin therapy and requires treatment with immunosuppressive agents. To examine the association between histologically confirmed IIM and current exposure to statin medications. Population-based case-control study using the South Australian Myositis Database of all histologically confirmed cases of IIM diagnosed between 1990 and 2014 in patients 40 years or older (n = 221) and population-based controls from the North West Adelaide Health Study (n = 662), matched by age and sex in a 3:1 ratio of controls to cases. Data analysis using conditional logistic regression was performed from June 1, 2016, to July 14, 2017. Current statin medication use. Unadjusted and adjusted (for diabetes and cardiovascular disease) odds ratios and 95% CIs for likelihood of inflammatory myositis. A total of 221 IIM cases met the inclusion criteria with a mean (SD) age of 62.2 (10.8) years, and 132 (59.7%) were female. Statin exposure at the time of IIM diagnosis was 68 of 221 patients (30.8%) and 142 of 662 matched controls (21.5%) (P = .005). There was an almost 2-fold increased likelihood of statin exposure in patients with IIM compared with controls (adjusted odds ratio, 1.79; 95% CI, 1.23-2.60; P = .001). Similar results were observed when patients with necrotizing myositis were excluded from the analysis (adjusted odds ratio, 1.92; 95% CI, 1.29-2.86; P = .001). In this large population-based study, statin exposure was significantly associated with histologically confirmed IIM. Given the increased use of statins worldwide and the severity of IIM, increased awareness and recognition of this potentially rare adverse effect of statin exposure is needed.