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Abstract Background There are health and well-being benefits of community ambulation; however, many older adults do not regularly walk outside of their home. Objectives were to estimate the associations between latent constructs related to community ambulation in older adults aged 65–85 (65+), and in adults with osteoarthritis (OA) aged 45–85. Methods Secondary data analysis of the comprehensive baseline and maintaining contact questionnaire data from the Canadian Longitudinal Study of Aging (CLSA) was completed. Based on a previous model of community ambulation post-stroke, structural equation modeling (SEM) was used to develop measurement and structural models for two groups: older adults 65+ and people with OA. Multi-group SEM was conducted to test measurement invariance across sex and age groups. Measurement models were developed for the following latent factors: ambulation (frequency of walking outside/week, hours walked/day, ability to walk without help, frequency and aids used in different settings); health perceptions (general health, pain frequency/intensity); timed functional mobility (gait speed, timed up-and-go, sit-to-stand, balance). Variables of depression, falls, age, sex, and fear of walking alone at night were covariates in the structural models. Results Data were used from 11,619 individuals in the 65+ group (mean age 73 years ±6, 49% female) and 5546 individuals in the OA group (mean age 67 ± 10, 60% female). The final 65+ model had a close fit with RMSEA (90% CI) = 0.018 (0.017, 0.019), CFI = 0.91, SRMR = 0.09. For the OA group, RMSEA (90% CI) = 0.021 (0.020, 0.023), CFI = 0.92, SRMR = 0.07. Health perceptions and timed functional mobility had a positive association with ambulation. Depression was associated with ambulation through negative associations with health perceptions and timed functional mobility. Multi-group SEM results reveal the measurement model was retained for males and females in the 65+ group, for males and females and for age groups (65+,

Abstract Background Mobility within and between life spaces is fundamental for health and well-being. Our objective was to verify a comprehensive framework for mobility. Methods This was a cross-sectional study. We used structural equation modeling to estimate associations between latent factors with data from the Canadian Longitudinal Study on Aging for participants 65–85 years of age (65+, n = 11,667) and for adults with osteoarthritis (OA) aged 45–85 (n = 5,560). Latent factors included life space mobility, and physical, psychosocial, environmental, financial, and cognitive elements. Personal variables (age, sex, education) were covariates. Results The models demonstrated good fit (65+: CFI = 0.90, RMSEA (90% CI) = 0.025 (0.024, 0.026); OA: CFI = 0.90, RMSEA (90% CI) = 0.032 (0.031, 0.033)). In both models, better psychosocial and physical health, and being less afraid to walk after dark (observed environmental variable) were associated with greater life space mobility. Greater financial status was associated with better psychosocial and physical health. Higher education was related to better cognition and finances. Older age was associated with lower financial status, cognition, and physical health. Cognitive health was positively associated with greater mobility only in the 65 + model. Models generated were equivalent for males and females. Conclusions Associations between determinants described in the mobility framework were verified with adults 65–85 years of age and in an OA group when all factors were considered together using SEM. These results have implications for clinicians and researchers in terms of important outcomes when assessing life space mobility; findings support interdisciplinary analyses that include evaluation of cognition, depression, anxiety, environmental factors, and community engagement, as well as physical and financial health. Public policies that influence older adults and their abilities to access communities beyond their homes need to reflect the complexity of factors that influence life space mobility at both individual and societal levels.

Abstract Background and Aims Hypertension is the leading preventable risk factor for cardiovascular disease, chronic kidney disease and cognitive impairment, and mortality and disability worldwide. Since prevention, early detection, and treatment of blood pressure improve public health, the aim of present study was to determine the best obesity indices and estimate the optimal cut‐off point for each one to predict the risk of elevated/stage 1 and undiagnosed hypertension in the population of center of Iran based on American ACC/AHA 2020 guidelines. Methods This cross‐sectional study was performed on 9715 people who enrolled in 2018 in Persian Adult Cohort in Shahedieh area of Yazd, Iran in 2018. The anthropometric indices including body mass index (BMI) and waist circumference (WC), wrist circumference, hip circumference, waist‐to‐hip ratio, and waist‐to height ratio of individuals, were extracted. The receiver operating characteristic curve was utilized to determine the optimum cut‐off point of each anthropometric index to predict hypertension stages and compare their predictive power by age‐sex categories. Statistical analysis was done using SPSS version 23.0. Results The results showed that BMI has the best predictive power to recognize the risk of elevated/stage 1 hypertension for female (area under the curve [AUC] = 0.72 and optimal cut‐off = 30.10 kg/m2) and WC for male (AUC = 0.66 and optimal cut‐off = 93.5 cm) in 35−45 age group. BMI had the best predictive power for the risk of undiagnosed hypertension for 35−45 years old male (AUC = 0.73 and optimal cut‐off = 28.90 kg/m2) and female (AUC = 0.75 and optimal cut‐off = 5.10 kg/m2), and hip circumference revealed similar predictive power for female as well (AUC = 0.75 and optimal cut‐off = 112 cm). Conclusion Based on our findings, BMI and WC, which are simple, inexpensive, and noninvasive means, are the best markers to predict the risk of elevated/stage 1 and undiagnosed hypertension in young Iranians. It shows that the approach of reducing hypertension prevalence through primary prevention, early detection, and enhancing its treatment is achievable.

Community ambulation is frequently limited for people with stroke. It is, however, considered important to people with stroke. The objectives were to identify factors associated with self-reported community ambulation in Canadians aged 45+ with stroke and to identify factors associated with community ambulation specific to Canadian males and to Canadian females with stroke. Data were utilized from the Canadian Longitudinal Study on Aging Tracking Cohort. Multivariate logistic regression models were developed for community ambulation. Mean age was 68 (SE 0.5) years (45% female). In the final community ambulation model (n = 855), factors associated with being less likely to 'walk outdoors sometimes or often' included difficulty or being unable to walk 2-3 blocks (decreased endurance) vs. no difficulty. Being more likely to walk outdoors was associated with 'better weather' months and being 55-64 years of age vs 75-85. Differences were noted between the models of only males and only females. Decreased walking endurance is associated with a decreased likelihood of walking in the community-a factor that can be addressed by rehabilitation professionals and in community based programs.

[This corrects the article DOI: 10.1371/journal.pone.0299569.].

Abstract Introduction The aim was to study any spatial and/or temporal patterns of ischemic heart disease (IHD) prevalence and measure the effects of selected social determinants on these spatial and space-time patterns. Methods Data were obtained from the Population Research Data Repository housed at the Manitoba Centre for Health Policy to identify persons who were diagnosed with IHD between 1995 and 2018. These persons were geocoded to 96 geographic regions of Manitoba. An area-level socioeconomic factor index (SEFI-2) and the proportion of the population who was Indigenous were calculated for each geographic region using the 2016 Canadian Census data. Associations between these factors and IHD prevalence were measured using Bayesian spatial Poisson regression models. Temporal trends and spatio-temporal trends were measured using Bayesian spatio-temporal Poisson regression models. Results Univariable models showed a significant association with increased regional Indigenous population proportion associated with a higher prevalence of IHD (RR: 0.07, 95% CredInt: (0.05, 0.10)) and for SEFI-2 (RR: 0.17, 95% CredInt: (0.11, 0.23)). Using a multivariable model, after accounting for the proportion of the population that was Indigenous, there was no evidence of an association between IHD prevalence and area-level socioeconomic factor. Spatio-temporal models showed no significant overall temporal trend in IHD prevalence, but there were significant spatially varying temporal trends within the 96 regions. Conclusions Association between Indigenous population proportion and IHD is consistent with previous research. No significant overall temporal trend was measured. However, regions with significantly increasing trends and significantly decreasing trends in IHD prevalence were identified.

Objective In studies of trajectories of physical functioning among older people, the data cannot be measured continuously, but only at certain time points in prespecified cycles. We examine how data collection cycles can affect the estimation of trajectories and their associations with survival.Study design and setting Longitudinal data from the Manitoba Follow-Up Study (MFUS), with 12 measurements collected annually from 2004 to 2015, are analysed using a summary measures of physical functioning from the Short Form-36 questionnaire. Based on the joint models of the functioning trajectories and risk of death, we compare the estimations among models using different frequency of data collection (annually, biennially and triennially).Results Our 2004 baseline includes 964 men who were survivors from the original MFUS cohort with mean age of 84 years and range between 75 and 94 years. Results from analysis of annual data indicate that the mean physical functioning is significantly decreasing over time. Further, the rate of decline is increasing over time. The current value of physical functioning is significantly associated with the hazard of death (p

Objectives Previous studies on depression in rural areas have yielded conflicting results. Features of rural areas may be conducive or detrimental to mental health. Our objective for this study was to determine if there are rural–urban disparities in depressive symptoms between those living in rural and urban areas of Canada.Design We conducted a cross-sectional analysis of a prospective cohort study, which is as representative as possible of the Canadian population—the Tracking Cohort of the Canadian Longitudinal Study on Aging. For this cohort, data were collected from 2010 to 2014. Data were analysed and results were obtained in 2020.Participants 21 241 adults aged 45–85.Measures Rurality was grouped as urban (n=11 772); peri-urban (n=2637); mixed (n=2125; postal codes with both rural and urban areas); and rural (n=4707). Depressive symptoms were measured using the 10-item Center for Epidemiological Studies-Depression. We considered age, sex, education, marital status and disease states as potential confounding factors.Results The adjusted beta coefficient was −0.24 (95% CI −0.42 to −0.07; p=0.01) for rural participants, −0.17 (95% CI −0.40 to 0.05; p=0.14) for peri-urban participants and −0.30 (95% CI −0.54 to −0.05; p=0.02) for participants in mixed regions, relative to urban regions. Risk factors associated with depressive symptoms were similar in rural and urban regions.Conclusions The small differences in depressive symptoms among those living in rural and urban regions are unlikely to be relevant at a clinical or population level. The findings do suggest some possible approaches to reducing depressive symptoms in both rural and urban populations. Future research is needed in other settings and on change in depressive symptoms over time.

Introduction: Understanding rural-urban differences, and understanding levels of life satisfaction in rural populations, is important in planning social and healthcare services for rural populations. The objectives of this study were to determine patterns of life satisfaction in Canadian rural populations aged 45-85 years, to determine rural-urban differences in life satisfaction across a rural-urban continuum after accounting for potential confounding factors and to determine if related social and health factors of life satisfaction differ in rural and urban populations. Methods: A secondary analysis was conducted using data from an ongoing population-based cohort study, the Canadian Longitudinal Study on Aging. A cross-sectional sample from the baseline wave of the tracking cohort was used, which was intended to be as generalizable as possible to the Canadian population. Four geographic areas were compared on a rural-urban continuum: rural, mixed (indicating some rural, but could also include some peri-urban areas), peri-urban, and urban. Life satisfaction was measured using the Satisfaction with Life Scale and dichotomized as satisfied versus dissatisfied. Other factors considered were province of residence, age, sex, education, marital status, living arrangement, household income, and chronic conditions. These factors were self-reported. Bivariate analyses using χ2 tests were conducted for categorical variables. Logistic regression models were constructed with the outcome of life satisfaction, after which a series of models were constructed, adjusting for province of residence, age, and sex, for sociodemographic factors, and for health-related factors. To report on differences in the factors associated with life satisfaction in the different areas, logistic regression models were constructed, including main effects for the variable of interest, for the variable rurality, and for the interaction term between these two variables. Results: Individuals living in rural areas were more satisfied with life than their urban counterparts (odds ratio (OR)=1.23; 95% confidence interval (CI): 1.13-1.35), even after accounting for the effect of confounding sociodemographic and health-related factors (OR=1.32, 95%CI: 1.19-1.45). Those living in mixed (OR=1.30, 95%CI: 1.14-1.49) and peri-urban (OR=1.21, 95%CI: 1.07-1.36) areas also reported being more satisfied than those living in urban areas. In addition, a positive association was found between life satisfaction and age, as well as between life satisfaction and being female. A strong graded association was noted between income and life satisfaction. Most chronic conditions were associated with lower life satisfaction. Finally, no major interaction was noted between rurality and each of the previously mentioned different factors associated with life satisfaction. Conclusion: Rural-urban differences in life satisfaction were found, with higher levels of life satisfaction in rural populations compared to urban populations. Preventing and treating common chronic illness, and also reducing inequalities in income, may prove useful to improving life satisfaction in both rural and urban areas. Studies of life satisfaction should consider rurality as a potential confounding factor in analyses of life satisfaction within and across societies.

Objective: To determine the prevalence of human immunodeficiency virus (HIV)-1 infections.