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.

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.

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.

The shaping of midlife women's views of health and health behaviors

The menopausal transition is a marker of aging for women and a time when health professionals urge women to prevent disease. In this research we adopted a constructivist, inductive approach in exploring how and why midlife women think about health in general, about being healthy, and about factors that influence engaging in healthy behaviors. The sample constituted 23 women who had participated in a women’s wellness program intervention trial and subsequent interviews. The women described lives of healthy eating and exercise, yet, their perceptions of health and healthy behavior at midlife contradicted that history. Midlife was associated with risk and guilt at not doing enough to be healthy. Health professionals provided a very limited frame within which to judge what is healthy. Mostly this was left up to individual women. Those who were successful framed health as “being able to do what you want to do when you want to do it.” In this article we present study findings of how meanings attached to health and being healthy were constructed through social expectations, family relationships, and life experiences.

Age, muscle fatigue, and walking endurance in pre-menopausal women

Aging is associated with loss of endurance; however, aging is also associated with decreased fatigue during maximal isometric contractions. The aims of this study were to examine the relationship between age and walking endurance (WE) and maximal isometric fatigue (MIF) and to determine which metabolic/fitness components explain the expected age effects on WE and MIF. Subjects were 96 pre-menopausal women. Oxygen uptake (walking economy) was assessed during a 3-mph walk; aerobic capacity and WE by progressive treadmill test; knee extension strength by isometric contractions, MIF during a 90-s isometric plantar flexion (muscle metabolism measured by 31P MRS). Age was related to increased walking economy (low VO2, r = −0.19, P < 0.03) and muscle metabolic economy (force/ATP, 0.34, P = 0.01), and reduced MIF (−0.26, P < 0.03). However, age was associated with reduced WE (−0.28, P < 0.01). Multiple regression showed that muscle metabolic economy explained the age-related decrease in MIF (partial r for MIF and age −0.13, P = 0.35) whereas walking economy did not explain the age-related decrease in WE (partial r for WE and age −0.25, P < 0.02). Inclusion of VO2max and knee endurance strength accounted for the age-related decreased WE (partial r for WE and age = 0.03, P > 0.80). In premenopausal women, age is related to WE and MIF. In addition, these results support the hypothesis that age-related increases in metabolic economy may decrease MIF. However, decreased muscle strength and oxidative capacity are related to WE.

Psychometric properties and health correlates of the Geriatric Anxiety Inventory in Australian community-residing older women

Abstract OBJECTIVE: To assess the psychometric properties and health correlates of the Geriatric Anxiety Inventory (GAI) in a cohort of Australian community-residing older women. METHOD: Cross-sectional study of a population-based cohort of women aged 60 years and over (N = 286). RESULTS: The GAI exhibited sound internal consistency and demonstrated good concurrent validity against the state half of the Spielberger State Trait Anxiety Inventory and the neuroticism domain of the NEO five-factor inventory. GAI score was significantly associated with self-reported sleep difficulties and perceived memory impairment, but not with age or cognitive function. Women with current DSM-IV Generalized Anxiety Disorder (GAD) had significantly higher GAI scores than women without such a history. In this cohort, the optimal cut-point to detect current GAD was 8/9. Although the GAI was designed to have few somatic items, women with a greater number of general medical problems or who rated their general health as worse had higher GAI scores. CONCLUSION: The GAI is a new scale designed specifically to measure anxiety in older people. In this Australian cohort of older women, the instrument had sound psychometric properties.

Cross-cultural comparisons of health-related quality of life in Australian and Japanese midlife women

Objective: The purpose of this study was to address (1) the existence of an association between menopausal status and the health-related quality of life (HRQOL) in Australian and Japanese women and (2) the relative contributions of menopausal status, modifiable lifestyle risk factors, health, and sociodemographic factors on HRQOL. Design: The Australian and Japanese Midlife Women's Health Study (AJMWHS) was a multisite, population-based study conducted in 2001 to 2002. Measures were conducted on data collected from a survey questionnaire used for a sample of women from Australia and Japan. HRQOL was assessed with seven subscales from the Short Form-36. Results: The differences seen in physical functioning, general health, and vitality are significant. The results support an effect of country of residence on physical functioning and general health. The impact of menopausal status on HRQOL was significantly associated with bodily pain and role-emotional. The country of residence did have a modifying effect on the relationship between menopausal status and physical functioning. After control for confounders, there was a significant difference between Australian and Japanese women for HRQOL. Menopausal status was not associated with HRQOL in the areas of general health and physical functioning. Modifiable lifestyle risk factors contributed more highly to HRQOL for the Australian women than for the Japanese women. If the women had a lowered body mass index, undertook physical activity, consumed dietary phytoestrogens, and used alcohol, their physical functioning seemed to be better. Differences were seen in the contributions to HRQOL in these areas, with lower body mass index in the Australian women and physical activity in the Japanese women being the highest predictors. Somatic and psychological symptoms seem to negatively affect both Japanese and Australian women's physical functioning, contributing more than sociodemographic factors, menopausal status, and behavioral determinants combined to general health and physical functioning. Conclusions: It is important that that consideration be given to incorporating the same tool within the cross-cultural design of studies so that comparisons between cultures and patterns of healthy aging can be made. The research suggests that there seems to be variations across Australian and Japanese midlife women in some areas of HRQOL and some factors that contribute to these areas.

The relationship between anti-mullerian hormone in women receiving fertility assessments and age at menopause in subfertile women : evidence from large population studies

Context: Anti-Müllerian hormone (AMH) concentration reflects ovarian aging and is argued to be a useful predictor of age at menopause (AMP). It is hypothesized that AMH falling below a critical threshold corresponds to follicle depletion, which results in menopause. With this threshold, theoretical predictions of AMP can be made. Comparisons of such predictions with observed AMP from population studies support the role for AMH as a forecaster of menopause. Objective: The objective of the study was to investigate whether previous relationships between AMH and AMP are valid using a much larger data set. Setting: AMH was measured in 27 563 women attending fertility clinics. Study Design: From these data a model of age-related AMH change was constructed using a robust regression analysis. Data on AMP from subfertile women were obtained from the population-based Prospect-European Prospective Investigation into Cancer and Nutrition (Prospect- EPIC) cohort (n � 2249). By constructing a probability distribution of age at which AMH falls below a critical threshold and fitting this to Prospect-EPIC menopausal age data using maximum likelihood, such a threshold was estimated. Main Outcome: The main outcome was conformity between observed and predicted AMP. Results: To get a distribution of AMH-predicted AMP that fit the Prospect-EPIC data, we found the critical AMH threshold should vary among women in such a way that women with low age-specific AMH would have lower thresholds, whereas women with high age-specific AMH would have higher thresholds (mean 0.075 ng/mL; interquartile range 0.038–0.15 ng/mL). Such a varying AMH threshold for menopause is a novel and biologically plausible finding. AMH became undetectable (�0.2 ng/mL) approximately 5 years before the occurrence of menopause, in line with a previous report. Conclusions: The conformity of the observed and predicted distributions of AMP supports the hypothesis that declining population averages of AMH are associated with menopause, making AMH an excellent candidate biomarker for AMP prediction. Further research will help establish the accuracy of AMH levels to predict AMP within individuals.

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.

Electrophoretic mobility of cell nuclei (EMN index) as a biomarker of the biological aging process: Considering the association between EMN index and age

The present study examined whether a specific property of cell microstructures may be useful as a biomarker of aging. Specifically, the association between age and changes of cellular structures reflected in electrophoretic mobility of cell nuclei index (EMN index) values across the adult lifespan was examined. This report considers findings from cross sections of females (n = 1273) aged 18–98 years, and males (n = 506) aged 19–93 years. A Biotest apparatus was used to perform intracellular microelectrophoresis on buccal epithelial cells collected from each individual. EMN index was calculated on the basis of the number of epithelial cells with mobile nuclei in reference to the cells with immobile nuclei per 100 cells. Regression analyses indicated a significant negative association between EMN index value and age for men (r = −0.71, p < 0.001) and women (r = −0.60, p < 0.001); demonstrating a key requirement that must be met by a biomarker of aging. The strength of association observed between EMN index and age for both men and women was encouraging and supports the potential use of EMN index for determining a biological age of an individual (or a group). In this study, a new attempt of complex explanation of cellular mechanisms contributing to age related changes of the EMN index was made. In this study, a new attempt of complex explanation of cellular mechanisms contributing to age related changes of the EMN index was made. EMN index has demonstrated potential to meet criteria proposed for biomarkers of aging and further investigations are necessary.