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Background and Objectives Prior research has highlighted the beneficial impact of social networks and social support on older adults' physical and psychosocial well-being. However, the impact of the relationship between chronic illness and social networks on the psychosocial well-being of older Nigerians remains understudied. This study explored how older Nigerians with chronic illnesses navigate the physical, mental, and emotional changes due to their chronic disease diagnosis within their social contexts. Research Design and Methods The current qualitative study used semistructured in-depth interviews with 19 purposively sampled older adults, aged 50 years and over, chronically ill, and receiving clinical care to examine the role of social networks in how chronically ill older Nigerians cope with their diagnosis. Results Three main themes reflecting participants' experiences emerged from the findings: (1) closely knit circles, (2) privacy and self-sufficiency, and (3) body image. Results show that chronically ill older Nigerians prefer to keep the knowledge of their conditions strictly within their close family circles. It was considered horrific to inform friends, community members, and religious groups about one's chronic illness. Findings further reveal that the need to appear healthy to one's social network stems from the fear of being discriminated against and attempts to maintain some level of normalcy when interacting with others. Additionally, feelings of inferiority and shame limited their participation in social activities and social network maintenance. Discussion and Implications We discuss the implications of the results for the mental well-being and quality of life of chronically ill older Nigerians and make recommendations for policies and resources that can improve the well-being of chronically ill Nigerians. [ABSTRACT FROM AUTHOR]

Background Mortality statistics using a single underlying cause of death (UC) are key health indicators. Rising multimorbidity and chronic disease mean that deaths increasingly involve multiple conditions. However, additional causes reported on death certificates are rarely integrated into mortality indicators, partly due to complexities in data and methods. This study aimed to assess trends and patterns in cause-related mortality in Australia, integrating multiple causes (MC) of death. Methods Deaths (n  = 1 773 399) in Australia (2006–17) were mapped to 136 ICD-10-based groups and MC indicators applied. Age-standardized cause-related rates (deaths/100 000) based on the UC (ASRUC) were compared with rates based on any mention of the cause (ASRAM) using rate ratios (RR = ASRAM/ASRUC) and to rates based on weighting multiple contributing causes (ASRW). Results Deaths involved on average 3.4 causes in 2017; the percentage with >4 causes increased from 20.9 (2006) to 24.4 (2017). Ischaemic heart disease (ASRUC = 73.3, ASRAM = 135.8, ASRW = 63.5), dementia (ASRUC = 51.1, ASRAM = 98.1, ASRW = 52.1) and cerebrovascular diseases (ASRUC = 39.9, ASRAM = 76.7, ASRW = 33.5) ranked as leading causes by all methods. Causes with high RR included hypertension (ASRUC = 2.2, RR = 35.5), atrial fibrillation (ASRUC = 8.0, RR = 6.5) and diabetes (ASRUC = 18.5, RR = 3.5); the corresponding ASRW were 12.5, 12.6 and 24.0, respectively. Renal failure, atrial fibrillation and hypertension ranked among the 10 leading causes by ASRAM and ASRW but not by ASRUC. Practical considerations in working with MC data are discussed. Conclusions Despite the similarities in leading causes under the three methods, with integration of MC several preventable diseases emerged as leading causes. MC analyses offer a richer additional perspective for population health monitoring and policy development. [ABSTRACT FROM AUTHOR]

Background: This study aims to describe the relationships between physical activity (PA), body composition, and multimorbidity over 10 years.Method: Participants (N = 373; 49% women; average age 61.3 ± 6.7 years) were followed for 10 years. Multimorbidity was defined by self-report as the presence of 2 or more of 12 listed chronic conditions. PA (steps per day) at baseline was assessed by pedometer, handgrip strength (HGS) by dynamometer, and appendicular lean mass (ALM) and total body fat mass by dual-energy x-ray absorptiometry. Relative HGS and ALM were calculated by dividing each body mass index (BMI). Regression cubic splines were used to assess evidence for a nonlinear relationship.Results: After 10 years, 45% participants had multimorbidity. There was a nonlinear relationship between PA and multimorbidity-PA was associated with lower multimorbidity risk among individuals who engaged in <10 000 steps/d (relative risk [RR] = 0.91, 95% CI: 0.85, 0.97, per 1 000 steps/d), but not among those who participated in ≥10 000 steps/d (RR = 1.04, 95% CI: 0.93, 1.09, per 1 000 steps/d). Higher BMI (RR = 1.05, 95% CI: 1.02, 1.08, per kg/m2) and fat mass (RR = 1.03, 95% CI: 1.01, 1.04, per kg), and lower relative HGS (RR = 0.85, 95% CI: 0.77, 0.94, per 0.1 psi/kg/m2) and ALM (RR = 0.93, 95% CI: 0.88, 0.98, per 0.1 kg/kg/m2) were linearly associated with a higher risk of multimorbidity. Absolute HGS and ALM were not significantly associated with multimorbidity.Discussion: These findings highlight the potential clinical importance of maintaining adequate levels of PA and of reducing adiposity and maintaining muscle function for minimizing the risk of multimorbidity in older adults. [ABSTRACT FROM AUTHOR]

Context: Vitamin D deficiency is a common, modifiable determinant of musculoskeletal health.Objective: There are limited data that examine the longitudinal change in population 25-hydroxyvitamin D (25[OH]D) and none that evaluate the long-term skeletal outcomes of longitudinal vitamin D status.Methods: A prospective cohort analysis was conducted of community-dwelling adults aged 50 to 80 years who had 25(OH)D assessed by radioimmunoassay and bone mineral density (BMD) by dual-energy x-ray absorptiometry at baseline (n = 1096), 2.5 (n = 870), and 10 (n = 565) years. Sun exposure was quantified by questionnaire and supplement use at clinic review. 25(OH)D less than 50 nmol/L was considered deficient. Participants were provided with their 25(OH)D results.Results: Over 10 years 25(OH)D increased (52.2 ± 17.0 to 63.5 ± 23.6 nmol/L, P < .001). Participants with baseline deficiency had larger 25(OH)D increases than baseline sufficient participants (19.2 ± 25.3 vs 1.6 ± 23.3 nmol/L, P < .001). Longitudinal change in 25(OH)D was associated with baseline summer (β = 1.46, P < .001) and winter (β = 1.29, P = .003) sun exposure, change in summer (β = 1.27, P = .002) and winter (β = 1.47, P < .001) sun exposure, and vitamin D supplement use (β = 25.0-33.0, P < .001). Persistent vitamin D sufficiency was associated with less BMD loss at the femoral neck (β = 0.020, P = .027), lumbar spine (β = 0.033, P = .003), and total hip (β = 0.023, P = .021) compared to persistent vitamin D deficiency. Achieving vitamin D sufficiency was associated with less BMD loss at the lumbar spine (β = 0.045, P < .001) compared to persistent vitamin D deficiency.Conclusions: Population 25(OH)D concentration increased because of a combination of increased sun exposure and supplement use. Maintaining or achieving vitamin D sufficiency was associated with less BMD loss over 10 years. [ABSTRACT FROM AUTHOR]

Background: The contribution of cerebral small vessel disease (cSVD) to the pathogenesis of frailty remains uncertain. We aimed to examine the associations between cSVD with progression of frailty in a population-based study of older people.Methods: People aged between 60 and 85 years were randomly selected form the electoral roll to participate in the Tasmanian Study of Cognition and Gait. Participants underwent self-reported questionnaires, objective gait, cognitive and sensorimotor testing over three phases ranging between 2005 and 2012. These data were used to calculate a 41-item frailty index (FI) at three time points. Baseline brain magnetic resonance imaging was performed on all participants to measure cSVD. Generalized mixed models were used to examine associations between baseline cSVD and progression of frailty, adjusted for confounders of age, sex, level of education, and total intracranial volume.Results: At baseline (n = 388) mean age was 72 years (SD = 7.0), 44% were female, and the median FI score was 0.20 (interquartile range [IQR] 0.12, 0.27). In fully adjusted models higher burden of baseline white matter hyperintensity (WMH) was associated with frailty progression over 4.4 years (β = 0.03, 95% CI: 0.01, 0.05; p = .004) independent of other SVD markers. Neither baseline infarcts (p = .23), nor microbleeds at baseline (p = .65) were associated with progression of frailty.Conclusions: We provide evidence for an association between baseline WMHs and progression of frailty. Our findings add to a growing body of literature suggesting WMH is a marker for frailty. [ABSTRACT FROM AUTHOR]

Aim: To describe the associations of between-person and within-person variability in serum 25-hydroxyvitamin D (25(OH)D), physical activity (PA), and knee pain and dysfunction with muscle mass, strength, and muscle quality over 10 years in community-dwelling older adults.Method: Participants (N = 1033; 51% women; mean age 63 ± 7.4 years) were measured at baseline, 2.5, 5, and 10 years. Lower limb lean mass (LLM) was assessed using dual energy X-ray absorptiometry, lower limb muscle strength (LMS) using a dynamometer, and lower limb muscle quality (LMQ) calculated as LMS/LLM. Knee pain and dysfunction were assessed using the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) index. PA was measured using pedometers. Linear-mixed effect regression models, with adjustment for confounders, were used to estimate the association of within-person and between-person variability in PA, 25(OH)D, and WOMAC scores with muscle mass, strength, and muscle quality.Results: Both between-person and within-person increases in PA were associated with LLM, LMS, and LMQ (all P < 0.05). Within-person and between-person increases in knee pain and dysfunction were associated with LLS and LMQ, but not with LLM (all P < 0.05). Between-person effects showed that higher average 25(OH)D was associated with a higher 10-year average LLM, LMS, and LMQ (all P < 0.05), whereas within-person increases in average 25(OH)D were associated with a higher LMS and LMQ, but not with LLM.Conclusions: Variability in 25(OH)D, pain, and dysfunction within an individual over time is related to muscle changes in that individual. Increasing one's own PA level further increases muscle mass, strength, and quality supporting the clinical recommendation of promoting PA to reduce age-related muscle loss. [ABSTRACT FROM AUTHOR]

Key contact person Dr Grace Joshy, Fellow, Research School of Population Health, Australian National University. Focus and outcomes for participants Mortality statistics are typically based on a single underlying cause of death (UCoD), derived from multiple conditions on the death certificate, and have provided critical evidence for policy and practice for over a century. There have been radical shifts in patterns of death in the past couple of decades; deaths in older ages are increasingly from chronic and degenerative diseases. The relevance of assuming that a single disease is causing the death is diminishing, especially with an aging population structure and increasing life expectancy. This symposium will enable participants to understand the complexities associated with mortality reporting/coding, strengths and limitations of available statistical methods for using multiple causes of death (MCoD) and the importance of quantifying mortality incorporating MCoD. Rationale for the symposium, including for its inclusion in the Congress The use of a single UCoD rather than MCoD means that vast amounts of potentially useful data are largely ignored, which is likely to bias mortality estimates (including under- and over-reporting of the importance of certain causes of death). Despite global recognition of the urgent need to better integrate data on MCoD into mortality statistics, use of these data are challenging and limited. Complexities arise from the way mortality information is reported on death certificates and coded to form mortality collections; limited understanding of available statistical methods also adds to the complexity. International Classification of Diseases 10th Revision (ICD-10) has been translated into 43 languages and it is being used by over 100 countries to report mortality data, a primary indicator of health status. The 2018 release of the 11th revision of the International Classification of Diseases, enriching data on multiple parameters including comorbidity, confers further urgency and a unique opportunity to optimise the use of MCoD in mortality reporting. The World Congress of Epidemiology 2020 will provide a unique platform for wider discussions on the challenges and opportunities for using MCoD data. The symposium will provide a deeper understanding and enhanced the use of MCoD data. The speakers are engaged in cutting-edge NHMRC-funded research on mortality incorporating MCoD and development of novel statistical methods. Presentation program The symposium will feature presentations from six speakers. Current mortality data constructs: strengths and limitations of the underlying causes of death by Mr James Eynstone-Hinkins, Director of Health and Vital Statistics at the Australian Bureau of Statistics. There are complexities around death certification, coding rules and the automated processing to select and code the underlying cause for each registered death. Strengths and limitations of the underlying causes of death will be discussed. MCoD: complexities, existing uses and future enhancements in classification by Ms Lauren Moran, Assistant Director of the Health and Vital Statistics Section at the Australian Bureau of Statistics. The presentation will describe some of the complexities associated with the rich MCoD data collection, its existing uses and future enhancements in classification and compilation. Quantifying mortality using MCoD: a review of existing methods and practice by Dr Saliu Balogun, Research Fellow at the Australian National University. A comprehensive literature review and audit summarising of the methodological approaches currently used to analyse MCoD data will be presented. The merits and limitations of the different analytical frameworks will be discussed. Mortality reporting incorporating MCoD: examples using Australia mortality collection 2006-2017 by Ms Karen Bishop, Research Fellow at the Australian National University. Data for 1.8 million deaths registered in 2006–2017 will be used with an extended classification of 136 causes of death. Standard mortality indicators such as age-standardised rate ratios of multiple to UCoD and cause of death association indicator will be used to outline the relative contribution of MCoD (vs UCoD) to mortality and the strength of comorbid disease associations. Survival analysis methods for modelling multi-cause mortality by Dr Margarita Moreno-Betancur ARC DECRA fellow, and Senior Research Fellow at The University of Melbourne and the Murdoch Children's Research Institute. This work developed the first formal survival analysis methods for modelling multiple-cause mortality, based on weighting methods that allow exploitation of all the readily-available data from death certificates. These methods enable the estimation of mortality rates for descriptive purposes as well as the conduct of Cox-type regression analyses for explanatory analyses. Pragmatic weighting strategies for MCoD: challenges and opportunities by Dr Grace Joshy, Senior Research Fellow at the Australian National University. Three weighting methods will be applied to the Australian mortality data: 1) traditional approach using UCoD alone; 2) UCoD and associated causes of death (ACoDs) equally weighted and (3) UCoD weighted 0.5 arbitrarily and remaining 0.5 apportioned to the remaining ACoDs. Challenges to further refining this weighting method by applying weights only to causes that are noted as 'contributory' (reported in Part II of death certificate) will be discussed. Names of presenters James Eynstone-Hinkins, Lauren Moran, Saliu Balogun, Karen Bishop, Margarita Moreno-Betancur, Grace Joshy [ABSTRACT FROM AUTHOR]

Background Four fifths of deaths in Australia involve multiple causes, but statistics typically use a single underlying cause of death (UC). The UC approach alone is insufficient for understanding the impact of non-underlying causes and identifying comorbid disease associations at death. Analysis of multiple causes of death (MC) is needed to measure the impact of all causes. We described MC patterns, considering cause-of-death coding and certification practices in Australia. Methods Using deaths registered in Australia from 2006 to 2017 (n = 1773525) coded to the International Classification of Diseases (ICD) and an extended classification (n = 136 causes) based on a World Health Organization short list, we described MCoD data by cause. Age-standardised rates based on UC and MC were compared using the standardised ratio of multiple to underlying causes (SRMU) to estimate the contribution of the cause to mortality compared to using the UC approach. Comorbidity was explored using the cause of death association indicator (CDAI) to compare the observed joint frequency of a contributory-underlying cause combined with expected frequency of the contributory cause (with any UC). Results On average 3.4 conditions caused each death and 24.4% of deaths had 5 plus causes. Largest SRMUs were for genitourinary diseases (8.0), blood diseases (7.8) and musculoskeletal conditions (6.7). CDAIs showed high associations between, for example, accidental alcohol and opioid poisoning, septicaemia and skin infections, and traumatic brain injury and falls. Conclusions MC indicators enhance measures of mortality and reassess the role of causes of death for descriptive and analytical epidemiology. Key messages This research demonstrates the value of MC analysis for Australian mortality data. [ABSTRACT FROM AUTHOR]

Background Mortality reporting and research are typically focused on a single underlying cause of death (UCoD) selected from multiple reported causes. The need to incorporate multiple causes of death (MCoD) in mortality statistics is now recognised internationally, but there is scant methodological work to guide analytical approaches. This review aims to identify and appraise current methods and practices used to analyse MCoD data. Methods The Web of Science, Medline, Pubmed and Scopus (from inception to December 2019) were queried. Studies reporting MCoD alone or in comparison with single UCoD were included. The review is supplemented by qualitative interview with international experts. Results 3491 studies were identified; 141 full texts were included in the review. The measures usually estimated when analysing MCoD can be broadly categorised into descriptive measures (n = 93 studies), measures of associations between diseases (n = 46 studies) and advanced statistical methods (n = 11 studies). Descriptive statistics commonly used include standardized ratio of multiple to underlying cause (SRMU) and mortality rates based on any mention of a disease. Approaches used to assess measures of associations between diseases include the Cause-of-Death Association Indicator (CDAI) and social network analysis. The advanced statistical methods include weighting MCoD and lethal defect-wear model of mortality. Audit results will be discussed. Conclusions This review provides a comprehensive and updated summary of methodological approaches used to analyse MCoD data. The merit of each analytical framework is discussed. Key messages More work is needed to develop methodological frameworks that could be used to support routine consideration of MCoD in practice. [ABSTRACT FROM AUTHOR]

Background Mortality statistics are typically based on a single underlying cause of death (UCoD). Although UCoD provides a useful construct, the relevance of assuming that a single disease caused the death is diminishing, especially with increased life expectancy and high proportions of deaths in older ages from chronic/degenerative diseases. Focussing on common underlying causes of death in Australia, we quantified mortality incorporating weighting strategies for multiple causes of death (MCoD). Methods All deaths registered in Australia from 2015-2017 (478,396 deaths) and coded using International Classification of Diseases Version 10 were classified using an extended cause list (n = 136 causes) based on a World Health Organization short list. Age-standardised rates (ASR) were estimated using three weighting methods: (1) traditional approach using UCoD alone; (2) UCoD and associated causes of death (ACoDs) equally weighted and (3) UCoD weighted 0.5 arbitrarily and remaining 0.5 apportioned to the remaining ACoDs. Results Common UCoD were ischaemic heart diseases, cerebrovascular diseases, dementia; 57671, 31515 and 27377 deaths respectively. There were substantial changes in ASR depending on the weighting method used. Variation in mortality patterns estimated using the three weighting methods and challenges to further refinement of the weighting strategy will be discussed. Conclusions Mortality indicators incorporating MCoD enhance traditional measures of mortality and provide a means to reassess the role of diseases in causing death. Further disease specific methods are required to refine current weighting strategies. Key messages Weighting strategies for are useful for quantifying mortality incorporating MCoD, but methodological challenges exist. [ABSTRACT FROM AUTHOR]