Modeling factors that influence exercise and dietary change among midlife Australian women: results from the Healthy Aging of Women Study

The objective of this study was to investigate the factors that influence midlife women to make positive exercise and dietary changes. In late 2005 questionnaires were mailed to 866 women aged 51–66 years from rural and urban locations in Queensland, Australia and participating in Stage 2 of the Healthy Aging of Women Study. The questionnaires sought data on socio-demographics, body mass index (BMI), chronic health conditions, self-efficacy, exercise and dietary behavior change since age 40, and health-related quality of life. Five hundred and sixty four (69%) were completed and returned by early 2006. Data analysis comprised descriptive and bivariate statistics and structural equation modeling. The results showed that midlife is a significant time for women to make positive health behavior changes. Approximately one-third of the sample (34.6%) indicated that they had increased their exercise and around 60% had made an effort to eat more healthily since age 40. Modeling showed self-efficacy to be important in making both exercise and dietary changes. Although education appeared to influence self-efficacy in relation to exercise change, this was not the case for dietary change. The study has application for programs promoting healthy aging among women, and implies that those with low education, high BMI and poor mental health may need considerable support to improve their lifestyles.

A longitudinal study of the relationship between lifestyle and mental health among midlife and older women in Australia : findings from the Healthy Aging of Women Study

We investigated the temporal relationship between lifestyle and mental health among 564 midlife women. The mental health measured included anxiety, depression, and mental well-being; the lifestyle measures included body mass index (BMI), exercise, smoking, alcohol use, and caffeine consumption. We found that BMI was positively related with mental well-being (r = .316, p = .009); smokers had lower mental well-being than nonsmokers (β = 6.725, p = .006), and noncaffeine drinkers had higher mental well-being (β = 5, p = .023). Past alcohol-drinkers had less anxiety than nondrinkers (β = 1.135, p = .04). Therefore, lifestyle is predictive of mental health among midlife and older women.

Predictors of mental health in post-menopausal women : results from the Australian healthy aging of women study

Objective: To examine the extent to which socio-demographics, modifiable lifestyle, and physical health status influence the mental health of post-menopausal Australian women. Methods: Cross-sectional data on health status, chronic disease and modifiable lifestyle factors were collected from a random cross-section of 340 women aged 60-70 years, residing in Queensland, Australia. Structural equation modelling (SEM) was used to measure the effect of a range of socio-demographic characteristics, modifiable lifestyle factors, and health markers (self-reported physical health, history of chronic illness) on the latent construct of mental health status. Mental health was evaluated using the Medical Outcomes Study Short Form 12 (SF-12®) which examined and Center for Epidemiologic Studies Depression Scale (CES-D). Results: The model was a good fit for the data (χ2=4.582, df=3, p=0.205) suggesting that mental health is negatively correlated with sleep disturbance (β = -0.612, p <0.001), and a history of depression (β = -0.141, p = 0.024).While mental health was associated with poor sleep, it was not correlated with most lifestyle factors (BMI, alcohol consumption, or cigarette smoking) or socio-demographics like age, income or employment category and they were removed from the final model. Conclusion: Research suggests that it is important to engage in a range of health promoting behaviours to preserve good health. We found that predictors of current mental health status included sleep disturbance, and past mental health problems, while socio-demographics and modifiable lifestyle had little impact. It may be however, that these factors influenced other variables associated with the mental health of post-menopausal women, and these relationships warrant further investigation.

A longitudinal study of the impact of chronic psychological stress on health-related quality of life and clinical biomarkers : protocol for the Australian Healthy Aging of Women Study

BACKGROUND: Despite advancements in our understanding of the importance of stress reduction in achieving good health, we still only have limited insight into the impact of stress on cellular function. Recent studies have suggested that exposure to prolonged psychological stress may alter an individual's physiological responses, and contribute to morbidity and mortality. This paper presents an overview of the study protocol we are using to examine the impact of life stressors on lifestyle factors, health-related quality of life and novel and established biomarkers of stress in midlife and older Australian women.The primary aim of this study is to explore the links between chronic psychological stress on both subjective and objective health markers in midlife and older Australian women. The study examines the extent to which exposure frightening, upsetting or stressful events such as natural disasters, illness or death of a relative, miscarriage and relationship conflict is correlated with a variety of objective and subjective health markers.Methods/design: This study is embedded within the longitudinal Healthy Aging of Women's study which has collected data from midlife and older Australian women at 5 yearly intervals since 2001, and uses the Allostastic model of women's health by Groer and colleagues in 2010. The current study expands the focus of the HOW study and will assess the impact of life stressors on quality of life and clinical biomarkers in midlife and older Australian women to explain the impact of chronic psychological stress in women. DISCUSSION: The proposed study hypothesizes that women are at increased risk of exposure to multiple or repeated stressors, some being unique to women, and the frequency and chronicity of stressors increases women's risk of adverse health outcomes. This study aims to further our understanding of the relationships between stressful life experiences, perceived quality of life, stress biomarkers, chronic illness, and health status in women.

Predictors of mental health in midlife and older women : results from the Australian Healthy Aging of Women Study

Purpose: To examine the extent to which socio-demographic characteristics, modifiable lifestyle factors and health status influence the mental health of midlife and older Australian women from the Australian Healthy Aging of Women (HOW) study. Methods: Data on health status, chronic disease and modifiable lifestyle factors were collected from a random sample of 340 women aged 40-65 years, residing in Queensland, Australia in 2011. Structural equation modelling (SEM) was used to measure the effect of a range of socio-demographic characteristics (marital status, age, income), modifiable lifestyle factors (caffeine intake, alcohol consumption, exercise, physical activity, sleep), and health markers (self-reported physical health, history of chronic illness) on the latent construct, mental health. Mental health was evaluated using the Medical Outcomes Study Short Form 12 (SF-12®) and the Center for Epidemiologic Studies Depression Scale (CES-D). Results: The model was a good fit for the data (χ2 = 40.166, df =312, p 0.125, CFI = 0.976, TLI = 0.950, RMSEA = 0.030, 90% CI = 0.000-0.053); the model suggested mental health was negatively influenced by sleep disturbance (β = -0.628), sedentary lifestyle (β = -0.137), having been diagnosed with one or more chronic illnesses (β = -0.203), and poor self-reported physical health (β = - 0.161). While mental health was associated with sleep, it was not correlated with many other lifestyle factors (BMI (β = -0.050), alcohol consumption (β = 0.079), or cigarette smoking (β = 0.008)) or background socio-demographic characteristics (age (β = 0.078), or income (β = -0.039)). Conclusion: While research suggests that it is important to engage in a range health promoting behaviours to preserve good health, we found that only sleep disturbance, physical health, chronic illness and level of physical activity predicted current mental health. However, while socio-demographic characteristics and modifiable lifestyle factors seemed to have little direct impact on mental health, they probably had an indirect effect.

What predicts mental health in midlife and older women? Results from the Australian Healthy Aging of Women Study

Objectives: Previous research has linked unhealthy lifestyle with a range of negative health outcomes in women. As women age however, they may have fewer performance expectations, but may view their health more positively. Clearly, the experiences of midlife and older women in relation to health and wellbeing need further exploration. The purpose of this study is to examine the factors associated with poor health-related quality of life in midlife (HRQoL) and older Australian women. Methods: The Australian longitudinal Healthy Aging of Women (HOW) study prospectively examines HRQoL, chronic disease and modifiable lifestyle factors midlife and older women as they age. Random sampling was used to select rural and urban based women from South-East Queensland, Australia. Data were collected from 386 women at three time points over the last decade (2001, 2004 and 2011). Results: The average age of women in this study was 65 years (SD = 2.82). Almost three-quarters (73%, n = 248) of the sample were married or living as though married, nine per cent (n = 30) were separated or divorced and a small proportion were had never married (n = 13). Most (86%, n = 291) of the women sample reported being Australian born, around one quarter (34%, n = 114) had completed additional study since leaving school (university degree or diploma). Over half (55%, n = 186) of participants were retired, one quarter (25%, n = 85) were in paid employment and the remained were unemployed (1%, n = 4), unable to work because of illness (2%, n = 6) or worked within the home (17%, n = 56). Using data collected over time we examined the relationship between a range of modifiable lifestyle factors and mental health using structural equation modelling. The overall model exhibited a good fit with the data. Poor sleep quality was associated with reduced mental health while better mental health was reported in women who exercised regularly and satisfied with their currently weight. As hypothesized, past mental health was a significant mediator of current mental health. Conclusions: These findings demonstrate that the mental health of women is complex and needs to be understood not only in terms of current lifestyle but also in relation to previously reported health status.

Prevalence and correlates of sleep disturbance in post-menopausal Australian women : the Healthy Aging of Women (HOW) study

Background: Sleep disturbance in midlife women has been studied extensively, although less is known about sleep after menopause. This study examined the relative impact of socio-demographics, modifiable lifestyle factors, and health status on sleep disturbance in post-menopausal women from Queensland, Australia. Methods: The longitudinal Healthy Aging of Women (HOW) study examines health-related quality of life (HRQOL measured by SF-12©), chronic illness, modifiable lifestyle factors such as physical activity, alcohol consumption, smoking, and sleep disturbance (General Sleep Disturbance Scale, GSDS ≥ 43 represent poor sleep) in midlife and older women from low and high socio-economic, rural and urban areas of South-East Queensland, Australia. This paper presents cross-sectional data from the 322 women, aged 60-70 years, participating in the HOW study in 2011. Results: For women in this study, sleep disturbance was relatively common, with 23% (n = 83) reporting poor sleeping (GSDS ≥ 43). Sleep disturbance scores were strongly correlated with being unemployed or on a disability support pension (β = 18.69, P < 0.01), sedentary lifestyle (β = 23.84, P < 0.01), and lower mental (β = -0.60, P <0.01) and physical health-related quality of life scores (β = -0.32, P = 0.01), and these variables explained almost one third of variance in sleep disturbance scores (ηρ² = 29%). Conclusions: Multivariable analysis revealed that sleep disturbance was correlated with physical and mental health-related quality of life, disability, and sedentary lifestyle, but not other lifestyle and socio-demographic characteristics. It may be however, that modifiable lifestyle factors may indirectly impact on sleep by influencing health status.

Stress, lifestyle and quality of life in midlife and older Australian women : results from the stress and the health of women study

Background Chronic psychological stress may pose a serious threat to health, although the mechanisms are not fully understood. This study examines the impact of stress on modifiable lifestyle factors, depressive symptoms, health-related quality of life (HRQOL) and chronic illness in older Australian women. Methods Cross-sectional data were collected from a random sample of 181 older adults aged 60-70 years from rural and urban areas of South-East Queensland, Australia. We used structural equation modelling to examine associations between stress, modifiable lifestyle factors, HRQoL, and chronic illness. Findings Parameter estimates show that older women who reported life stressors where they felt helpless and feared for their life (high magnitude stressors) also reported higher body mass index (p = 0.03) and more chronic illness (p <0.01). In contrast, duration of exposure to life stressors was associated with higher depressive symptom scores (CES-D, p = 0.02) and sleep disturbance scores (p <0.01). Conclusions Our findings support the link between traumatic personal histories (exposure to high magnitude stressors) and unhealthy lifestyle factors. Findings highlight the need for more research on how stress reduction healthy lifestyle and positive coping strategies can be used to reduce the effects of high magnitude stress on health-related quality of life and chronic illness.

Cognitive reserve is associated with the functional organization of brain networks in healthy aging: a MEG study

The proportion of elderly people in the population has increased rapidly in the last century and consequently "healthy aging" is expected to become a critical area of research in neuroscience. Evidence reveals how healthy aging depends on three main behavioral factors: social lifestyle, cognitive activity and physical activity. In this study, we focused on the role of cognitive activity, concentrating specifically on educational and occupational attainment factors, which were considered two of the main pillars of cognitive reserve. 21 subjects with similar rates of social lifestyle, physical and cognitive activity were selected from a sample of 55 healthy adults. These subjects were divided into two groups according to their level of cognitive reserve; one group comprised subjects with high cognitive reserve (9 members) and the other contained those with low cognitive reserve (12 members). To evaluate the cortical brain connectivity network, all participants were recorded by Magnetoencephalography (MEG) while they performed a memory task (modified version of the Sternberg¿s Task). We then applied two algorithms (Phase Locking Value & Phase-Lag Index) to study the dynamics of functional connectivity. In response to the same task, the subjects with lower cognitive reserve presented higher functional connectivity than those with higher cognitive reserve. These results may indicate that participants with low cognitive reserve needed a greater 'effort' than those with high cognitive reserve to achieve the same level of cognitive performance. Therefore, we conclude that cognitive reserve contributes to the modulation of the functional connectivity patterns of the aging brain.

Relationship Between Regional Brain Volumes and Cognitive Performance in the Healthy Aging: An MRI Study Using Voxel-Based Morphometry

The presence of cognitive impairment is a frequent complaint among elderly individuals in the general population. This study aimed to investigate the relationship between aging-related regional gray matter (rGM) volume changes and cognitive performance in healthy elderly adults. Morphometric magnetic resonance imaging (MRI) measures were acquired in a community-based sample of 170 cognitively-preserved subjects (66 to 75 years). This sample was drawn from the "Sao Paulo Ageing and Health" study, an epidemiological study aimed at investigating the prevalence and risk factors for Alzheimer's disease in a low income region of the city of Sao Paulo. All subjects underwent cognitive testing using a cross-culturally battery validated by the Research Group on Dementia 10/66 as well as the SKT (applied on the day of MRI scanning). Blood genotyping was performed to determine the frequency of the three apolipoprotein E allele variants (APOE epsilon 2/epsilon 3/epsilon 4) in the sample. Voxelwise linear correlation analyses between rGM volumes and cognitive test scores were performed using voxel-based morphometry, including chronological age as covariate. There were significant direct correlations between worse overall cognitive performance and rGM reductions in the right orbitofrontal cortex and parahippocampal gyrus, and also between verbal fluency scores and bilateral parahippocampal gyral volume (p < 0.05, familywise-error corrected for multiple comparisons using small volume correction). When analyses were repeated adding the presence of the APOE epsilon 4 allele as confounding covariate or excluding a minority of APOE epsilon 2 carriers, all findings retained significance. These results indicate that rGM volumes are relevant biomarkers of cognitive deficits in healthy aging individuals, most notably involving temporolimbic regions and the orbitofrontal cortex.

Breastfeeding self-efficacy of women using second-line strategies for healthy term infants in the first week postpartum : an Australian observational study

Background Breastfeeding self-efficacy (BFSE) supports breastfeeding initiation and duration. Challenges to breastfeeding may undermine BFSE, but second-line strategies including nipple shields, syringe, cup, supply line and bottle feeding may support breastfeeding until challenges are resolved. The primary aim of this study was to examine BFSE in a sample of women using second-line strategies for feeding healthy term infants in the first week postpartum. Methods A retrospective self-report study was conducted using the Breastfeeding Self-Efficacy Scale - Short Form (BSES-SF), demographic and infant feeding questionnaires. Breastfeeding women who gave birth to a singleton healthy term infant at one private metropolitan birthing facility in Australia from November 2008 to February 2009 returned anonymous questionnaires by mail. Results A total of 128 (73 multiparous, 55 primiparous) women participated in the study. The mean BSES-SF score was 51.18 (Standard deviation, SD: 12.48). The median BSES-SF score was 53. Of women using a second-line strategy, 16 exceeded the median, and 42 were below. Analyses using Kruskal-Wallis tests confirmed this difference was statistically significant (H = 21.569, p = 0.001). The rate of second-line strategy use was 48%. The four most commonly used second-line strategies were: bottles with regular teats (77%); syringe feeding (44%); bottles with wide teats (34%); and nipple shields (27%). Seven key challenges were identified that contributed to the decision to use second-line strategies, including: nipple pain (40%); unsettled infant (40%); insufficient milk supply (37%); fatigue (37%); night nursery care (25%); infant weight loss > 10% (24%); and maternal birth associated pain (20%). Skin-to-skin contact at birth was commonly reported (93%). At seven days postpartum 124 women (97%) were continuing to breastfeed. Conclusions The high rate of use of second-line strategies identified in this study and high rate of breastfeeding at day seven despite lower BFSE indicate that such practices should not be overlooked by health professionals. The design of this study does not enable determination of cause-effect relationships to identify factors which contribute to use of second-line strategies. Nevertheless, the significantly lower BSES-SF score of women using a second-line strategy highlights this group of women have particular needs that require attention.

Genetics of Healthy Aging in Europe.The EU-Integrated Project GEHA (GEnetics of Healthy Aging)

The aim of the 5-year European Union (EU)-Integrated Project GEnetics of Healthy Aging (GEHA), constituted by 25 partners (24 from Europe plus the Beijing Genomics Institute from China), is to identify genes involved in healthy aging and longevity, which allow individuals to survive to advanced old age in good cognitive and physical function and in the absence of major age-related diseases. To achieve this aim a coherent, tightly integrated program of research that unites demographers, geriatricians, geneticists, genetic epidemiologists, molecular biologists, bioinfomaticians, and statisticians has been set up. The working plan is to: (a) collect DNA and information on the health status from an unprecedented number of long-lived 90+ sibpairs (n = 2650) and of younger ethnically matched controls (n = 2650) from 11 European countries; (b) perform a genome-wide linkage scannning in all the sibpairs (a total of 5300 individuals); this investigation will be followed by linkage disequilibrium mapping (LD mapping) of the candidate chromosomal regions; (c) study in cases (i.e., the 2650 probands of the sibpairs) and controls (2650 younger people), genomic regions (chromosome 4, D4S1564, chromosome 11, 11.p15.5) which were identified in previous studies as possible candidates to harbor longevity genes; (d) genotype all recruited subjects for apoE polymorphisms; and (e) genotype all recruited subjects for inherited as well as epigenetic variability of the mitochondrial DNA (mtDNA). The genetic analysis will be performed by 9 high-throughput platforms, within the framework of centralized databases for phenotypic, genetic, and mtDNA data. Additional advanced approaches (bioinformatics, advanced statistics, mathematical modeling, functional genomics and proteomics, molecular biology, molecular genetics) are envisaged to identify the gene variant(s) of interest. The experimental design will also allow (a) to identify gender-specific genes involved in healthy aging and longevity in women and men stratified for ethnic and geographic origin and apoE genotype; (b) to perform a longitudinal survival study to assess the impact of the identified genetic loci on 90+ people mortality; and (c) to develop mathematical and statistical models capable of combining genetic data with demographic characteristics, health status, socioeconomic factors, lifestyle habits.

Genome-wide linkage analysis for human longevity: Genetics of healthy aging study

Clear evidence exists for heritability of humanlongevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome-wide linkage scan thus far reported. Linkage analyses included 2118nonagenarian Caucasian sibling pairs that have been enrolled in 15 study centers of 11 European countries as part of the Genetics of Healthy Aging (GEHA) project. In the joint linkage analyses, we observed four regions that show linkage with longevity; chromosome 14q11.2 (LOD = 3.47), chromosome 17q12-q22 (LOD = 2.95), chromosome 19p13.3-p13.11 (LOD = 3.76), and chromosome 19q13.11-q13.32 (LOD = 3.57). To fine map these regions linked to longevity, we performed association analysis using GWAS data in a subgroup of 1228 unrelated nonagenarian and 1907 geographically matched controls. Using a fixed-effect meta-analysis approach, rs4420638 at the TOMM40/ APOE/APOC1 gene locus showed significant association with longevity (P-value = 9.6 × 10). By combined modeling of linkage and association, we showed that association of longevity with APOEe4 and APOEe2 alleles explain the linkage at 19q13.11-q13.32 with P-value = 0.02 and P-value = 1.0 × 10, respectively. In the largest linkage scan thus far performed for human familial longevity, we confirm that the APOE locus is a longevity gene and that additional longevity loci may be identified at 14q11.2, 17q12-q22, and 19p13.3-p13.11. As the latter linkage results are not explained by common variants, we suggest that rare variants play an important role in human familial longevity.

‘Healthy mobile check-ins’ study: using GIS in smartphones to track use of urban environment by survivors of endometrial cancer

Aims/Objectives Our study aims to test the capacity of a newly developed smartphone innovation to obtain data on social, structural, and spatial determinants of the daily health-related behaviours of women living in urban Brisbane neighbourhoods who have survived endometrial cancer. Methods The women used a mobile web app designed specifically for the project to record GIS/location data on every destination they visited within their local urban neighbourhoods over a two-week period. Additionally, we gathered textual data on the social context/reasons for travel, as well as mode of transport to reach these destinations. The data was transported to SPSS and Google Earth for statistical and spatial analysis. We then met with the women to discuss lifestyle interventions to maximise their use of their local neighbourhoods in ways that could increase their physical activity levels and improve their overall health and well-being. These interventions will be evaluated and translated into a large-scale national study if effective. Results Initial findings about patterns in the group’s use of the local urban environment will be displayed, including daily distances travelled, types of locations visited, walking levels, use of public transport, use of green spaces and use of health-related resources. Any socio-demograpahic differences found between the women will be reported. Qualitative, quantitative, and spatial/mapping data will be displayed Conclusion The benefits and limitations of the mobile website designed to collect a range of data types about human-neighbourhood interactions with implications for intervention design will be discussed.

Evaluation of the effect of wheat aleurone-rich foods on markers of antioxidant status, inflammation and endothelial function in apparently healthy men and women

Observational data show an inverse association between the consumption of whole-grain foods, and inflammation and related diseases. Although the underlying mechanisms are unclear, whole grains, and in particular the aleurone layer, contain a wide range of components with putative antioxidant and anti-inflammatory effects. We evaluated the effects of a diet high in wheat aleurone on plasma antioxidants status, markers of inflammation and endothelial function. In this parallel, participant-blinded intervention, seventy-nine healthy, older, overweight participants (45-65 years, BMI>25 kg/m²) incorporated either aleurone-rich cereal products (27 g aleurone/d), or control products balanced for fibre and macronutrients, into their habitual diets for 4 weeks. Fasting blood samples were taken at baseline and on day 29. Results showed that, compared to control, consumption of aleurone-rich products provided substantial amounts of micronutrients and phytochemicals which may function as antioxidants. Additionally, incorporating these products into a habitual diet resulted in significantly lower plasma concentrations of the inflammatory marker, C-reactive protein (P = 0·035), which is an independent risk factor for CVD. However, no changes were observed in other markers of inflammation, antioxidant status or endothelial function. These results provide a possible mechanism underlying the beneficial effects of longer-term whole-grain intake. However, it is unclear whether this effect is owing to a specific component, or a combination of components in wheat aleurone.