Erratum. Does Attraction Toward Physical Activity Predict Physical Activity Behavior in Older Adults?

IntroductionThe influence of the COVID-19 pandemic on physical activity behaviour in older adults is of particular concern. However, little is yet known about how pre-existing socioeconomic inequalities in older adults’...

Fatigue has been associated with reductions in daily activity of older people. Summary measures of daily physical activity provide limited understanding of how fatigue affects physical activity behavior. This study examined the hour-by-hour energy expenditure estimated from accelerometry data to provide insight into physical activity behaviors of older people experiencing fatigue. Fatigued participants were matched to 'not fatigued' participants by age, sex, and BMI. Each group consisted of 86 people with a mean age 73.8 years (SD 2.0), BMI 26.5 kg⋅m-2 (SD 3.9) and 61% female. The phase-space plot, constructed to express rate of change of average vertical axis counts per hour as a time series, showed fatigued participants deviated from the not fatigued participants during the morning period, when hour-by-hour activity was increasing. Older people who feel fatigued have a different morning activity pattern, which appears to lead to the lower overall levels of physical activity.

The relationship between attitudes, beliefs and physical activity behaviour in older adults with knee pain

Intervening on physical activity and sedentary behavior in older adults.

Epidemiological evidence suggests that physical activity (PA) can improve the health, physical function and the quality of life of older adults. Several modes of PA have been highlighted as particularly beneficial for these outcomes, but the challenges of engaging and sustaining participation limit their effectiveness. Therefore, the aim of this study was to determine barriers and opinions to regularly engaging in different types of PA using taster sessions to provide recommendations on how to engage and sustain PA behaviour in older adults. A multi-phase, mixed-method study design on 12 older adults was used to gain insight into older adult's perceptions of five types of PA (two sports, resistance exercise, exergaming, yoga and home-based exercise). Perceptions of these types of PA were collected pre-taster sessions and were re-evaluated after all taster sessions using questionnaires and focus groups. Triangulation of data revealed that in general, all PA types were enjoyed, but yoga was least popular. Pre-taster sessions, home-based exercise and resistance exercise were most popular whereas following the taster sessions, preferences were for exergaming, resistance exercise and sports. Our data highlights the effective utility of taster sessions and combined with other literature; we present several key recommendations to help to improve engagement in long-term PA behaviour in various PA types. These include ensuring adequate social interaction between similarly aged and ability capable older adults during PA. Having appropriate supervisors, and advertising and facilitating PA opportunities, considering the needs of individuals, providing motivational strategies and providing continued accountability.

The HiBalance program is a progressive and highly challenging balance training intervention incorporating Parkinson's disease (PD) specific balance components. The program improves balance and gait and increases the amount of ambulation in short-term, in older adults with PD. Yet, potential short- and long-term effects on habitual physical activity and sedentary behavior are currently unidentified. The aim of this study was to conduct preplanned secondary analyses of short- and long-term effects of the HiBalance program on objectively measured amount and bouts of brisk walking, sedentary behavior, and total physical activity in older adults with PD. Further, our aim was to investigate demographic, intervention-related, disease-related, and function-related factors potentially related to a difference in activity after intervention. A total of 100 older adults with mild-moderate PD were recruited. The intervention group participated in the HiBalance program, and the control received care as usual and was offered the HiBalance program after study termination. Physical activity data were collected using accelerometers at baseline, after intervention and after 6 and 12 months. A multilevel model was utilized to investigate the postintervention and long-term (6 and 12 months) effects on total physical activity, amount and bouts of brisk walking (i.e., moderate intensity physical activity), and sedentary behavior. Between-group difference for the main outcome brisk walking was at postintervention: Δ −10, CI −23.78 to 3.69 min/day (p < 0.05); 6 months: Δ −10, CI −23.89 to 3.89 min/day (p < 0.05); and 12 months: Δ −4, CI −16.81 to 8.81 min/day (p=0.43). Being part of the intervention group as well as finishing training during spring/summer showed an independent association to increased brisk walking after the intervention period. In conclusion, the HiBalance program increases the physical activity on moderate intensity after intervention and at 6 months but not at 12 months, independently of improved balance. Season seems to influence the effect on the physical activity.

The aim was to explore the self-reported impact of the COVID-19 pandemic on nutrition and physical activity behaviour in Dutch older adults and to identify subgroups most susceptible to this impact. Participants (N = 1119, aged 62–98 y, 52.8% female) of the Longitudinal Aging Study Amsterdam living independently completed a COVID-19 questionnaire. Questions on diagnosis, quarantine and hospitalization were asked, as well as impact of the pandemic on ten nutrition and physical activity behaviours. Associations of pre-COVID-19 assessed characteristics (age, sex, region, household composition, self-rated health, BMI, physical activity, functional limitations) with reported impact were tested using logistic regression analyses. About half of the sample (48.3–54.3%) reported a decrease in physical activity and exercise due to the pandemic. An impact on nutritional behaviour predisposing to overnutrition (e.g., snacking more) was reported by 20.3–32.4%. In contrast, 6.9–15.1% reported an impact on behaviour predisposing to undernutrition (e.g., skipping warm meals). Those who had been in quarantine (n = 123) more often reported a negative impact. Subgroups with higher risk of impact could be identified. This study shows a negative impact of the COVID-19 pandemic on nutrition and physical activity behaviour of many older adults, which may increase their risk of malnutrition, frailty, sarcopenia and disability.

Ecological momentary assessment (EMA) is a methodological tool that can provide novel insights into the prediction and modeling of physical behavior; however, EMA has not been used to study physical activity (PA) or sedentary behavior (SB) among racial minority older adults. This study aimed to determine the feasibility and validity of an EMA protocol to assess racial minority older adults’ PA and SB. For 8 days, older adults (n = 91; 89% African American; 70% earning &lt;$20,000/year) received six randomly prompted, smartphone-based EMA questionnaires per day and wore an activPAL monitor to measure PA and SB. The PA and SB were also self-reported through EMA. Participants were compliant with the EMA protocol on 92.4% of occasions. Participants were more likely to miss an EMA prompt in the afternoon compared to morning and on weekend days compared to weekdays. Participants were less likely to miss an EMA prompt when engaged in more device-based SB in the 30 min around the prompt. When participants self-reported PA, they engaged in less device-based PA in the 15 min after compared to the 15 min before the EMA prompt, suggesting possible reactance or disruption of PA. EMA-reported PA and SB were positively associated with device-based PA and SB in the 30 min around the EMA prompt, supporting criterion validity. Overall, the assessment of low-income, African American older adults’ PA and SB through EMA is feasible and valid, though physical behaviors may influence compliance and prompting may create reactivity.

Increasing self-efficacy is an effective mechanism for increasing physical activity, especially for older people. The aim of this review was to identify behaviour change techniques (BCTs) that increase self-efficacy and physical activity behaviour in non-clinical community-dwelling adults 60years or over. A systematic search identified 24 eligible studies reporting change in self-efficacy for physical activity following an intervention. Moderator analyses examined whether the inclusion of specific BCTs (as defined by CALO-RE taxonomy) was associated with changes in self-efficacy and physical activity behaviour. Overall, interventions increased self-efficacy (d = 0.37) and physical activity (d = 0.14). Self-regulatory techniques such as setting behavioural goals, prompting self-monitoring of behaviour, planning for relapses, providing normative information and providing feedback on performance were associated with lower levels of both self-efficacy and physical activity. Many commonly used self-regulation intervention techniques that are effective for younger adults may not be effective for older adults.

Mild cognitive impairment (MCI) represents a transition between normal cognitive aging and dementia and may represent a critical time frame for promoting cognitive health through behavioral strategies. Current evidence suggests that physical activity (PA) and sedentary behavior are important for cognition. However, it is unclear whether there are differences in PA and sedentary behavior between people with probable MCI and people without MCI or whether the relationships of PA and sedentary behavior with cognitive function differ by MCI status. The aims of this study were to examine differences in PA and sedentary behavior between people with probable MCI and people without MCI and whether associations of PA and sedentary behavior with cognitive function differed by MCI status. This was a cross-sectional study. Physical activity and sedentary behavior in adults dwelling in the community (N = 151; at least 55 years old) were measured using a wrist-worn actigraphy unit. The Montreal Cognitive Assessment was used to categorize participants with probable MCI (scores of <26/30) and participants without MCI (scores of ≥26/30). Cognitive function was indexed using the Alzheimer Disease Assessment Scale-Cognitive-Plus (ADAS-Cog Plus). Physical activity and sedentary behavior were compared based on probable MCI status, and relationships of ADAS-Cog Plus with PA and sedentary behavior were examined by probable MCI status. Participants with probable MCI (n = 82) had lower PA and higher sedentary behavior than participants without MCI (n = 69). Higher PA and lower sedentary behavior were associated with better ADAS-Cog Plus performance in participants without MCI (β = -.022 and β = .012, respectively) but not in participants with probable MCI (β < .001 for both). This study was cross-sectional and therefore could not establish whether conversion to MCI attenuated the relationships of PA and sedentary behavior with cognitive function. The diagnosis of MCI was not confirmed with a physician; therefore, this study could not conclude how many of the participants categorized as having probable MCI would actually have been diagnosed with MCI by a physician. Participants with probable MCI were less active and more sedentary. The relationships of these behaviors with cognitive function differed by MCI status; associations were found only in participants without MCI.

Ecological momentary assessment (EMA) has the potential to yield new insights into the prediction and modeling of physical activity (PA) and sedentary behavior (SB). The objective of this study was to determine the feasibility and validity of an EMA protocol to assess older adults’ PA and SB. Feasibility was determined by examining factors associated with EMA survey compliance and if PA or SB were impacted by EMA survey compliance. Validity was determined by comparing EMA-reported PA and SB to objectively measured PA and SB at the EMA prompt. Over 10 days, older adults (n = 104; Agerange = 60–98 years) received 6 randomly prompted EMA questionnaires on a smartphone each day and wore an ActivPAL activity monitor to provide a device-based measure of PA and SB. Participants reported whether they were currently engaged in PA or SB. Older adults were compliant with the EMA and ActivPAL protocol on 92% of occasions. Differences in EMA compliance differed by weight status. Among overweight and obese older adults EMA compliance differed by sex (OR = 3.15, 95% CI: 1.43, 6.92) and day of week (OR = 1.79, 95% CI: 1.33, 2.41). Among normal weight older adults, EMA compliance differed by time of day (OR = 1.52, 95% CI: 1.02, 2.30). EMA compliance did not differ for device-based PA or SB in the 15 min before versus the 15 min after the EMA prompt, suggesting that these behaviors did not influence likelihood of responding and responding did not influence these behaviors (ps > 0.05). When PA was reported through EMA, participants engaged in less device-based PA in the 15 min after compared to the 15 min before the EMA prompt (p = 0.01), suggesting possible reactance or a disruption of PA. EMA-reported PA and SB were positively associated with higher device-based PA and SB in the ±15 min, respectively, supporting criterion validity (ps < 0.05). The assessment of older adults’ PA and SB through EMA is feasible and valid, although there may be PA reactance to EMA prompting. Therefore, EMA represents a significant methodological tool that can aid in our understanding of the environmental, social, and psychological processes regulating older adults’ PA and SB in the context of everyday life.

Age-related hearing loss is common among older adults and may influence physical activity and sedentary behaviors, such as TV viewing. This study examined whether a hearing intervention could affect these behaviors over 3 years. A total of 977 participants (mean age of 76.8, 53.5% female, 11.5% Black), recruited from the ARIC study (n = 238) and de novo (n = 739) with hearing loss (pure-tone average = 39.4 dB), were randomized to a hearing intervention or a health education control group. Physical activity, leisurely walking, and TV viewing were interrogated at baseline and 3-year follow-up. We used regression models adjusted for demographic and hearing loss severity to examine the impact of the intervention on the change in the frequency of engaging in these activities. At baseline, 57.6% of participants engaged in moderate-to-vigorous physical activity (MVPA), 29.1% in high-frequency leisurely walking, and 46.8% in high-frequency TV viewing. Over 3 years, MVPA decreased to 48.8%, whereas leisurely walking and TV viewing increased. After 3 years, the hearing intervention group had similar odds of engaging in MVPA (ratio of odds ratios [ROR] = 1.03, 95% confidence interval [CI], 0.93-1.14), leisurely walking (ROR = 1.04, 95% CI, 0.93-1.17), and TV viewing (ROR = 0.95, 95% CI, 0.87-1.02) compared with the control group. Results were consistent across recruitment sources (ARIC and de novo). A hearing intervention did not significantly influence physical activity, walking, or TV viewing behaviors in older adults over 3 years. Additional strategies may be needed to change physical and sedentary behaviors in this population.

Since the initial scientific statement on Secondary Prevention of Coronary Heart Disease (CHD) in the Elderly was published in 2002,1 several trends have continued that make an update highly appropriate. First, the graying of the US population and those of other industrialized countries has progressed unabated because more adults are surviving into their senior years. The number of Americans aged ≥75 years was estimated at 18.6 million in 2010, representing ≈6% of the population,2 and it is expected to double by 2050. The population aged ≥85 years is growing the most rapidly, with numbers expected to reach 19.5 million by 2040. In 2008, 67% of the 811 940 cardiovascular deaths in the United States occurred in people aged ≥75 years.3 In parallel to this increase in the older adult demographic, the number of Americans with CHD has increased to an estimated 16.3 million, more than half of whom are >65 years of age.3 Similarly, 7 million have had a stroke, the incidence of which approximately doubles with successive age decades after 45 to 54 years.3 Peripheral artery disease (PAD) affects 8 to 10 million Americans, the majority of whom are >65 years of age. Between 2015 and 2030, annual US costs related to atherosclerotic cardiovascular disease (ASCVD) are projected to increase from $84.8 billion to $202 billion.3 Moreover, given that ASCVD often undermines functional capacity and independence and increases reliance on long-term care, indirect expenses related to ASCVD are also expected to increase. Thus, the need for effective secondary prevention measures in the older adult population with known ASCVD has never been greater. Notably, the 2011 American Heart Association (AHA)/American College of Cardiology Foundation (ACCF) updated guidelines for secondary prevention of CHD broadened …

There is limited evidence for the associations of area-level crime with older adults’ physical activity and sedentary behavior, especially in Asia. This study explored the association of area-level crime with older adults’ active and sedentary behavior. A telephone-based survey of Taiwanese seniors was conducted in September–November of 2017. Data related to sociodemographic factors, residential neighborhood (objectively recorded area-level crime incidence), and time spent in physical activity and sedentary behavior, were obtained from 1068 older adults. Adjusted binary logistic regression was analyzed. Fully adjusted analyses showed older adults living in neighborhoods with a higher incidence of drug crime (odds ratio, OR = 0.71, 95% confidence interval, CI = 0.52–0.96), car theft (OR = 0.70, 95% CI 0.51–0.95), and locomotive theft (OR = 0.69, 95% CI 0.51–0.94) were found to be less likely to achieve the recommendation on physical activity. In addition, those living in neighborhoods with a higher incidence of theft (OR = 1.93, 95% CI 1.05–3.55), drug crime (OR = 1.93, 95% CI 1.05–3.55), breaking and entering (OR = 2.04, 95% CI 1.11–3.76), and rape (OR = 2.20, 95% CI 1.20–4.06) were more likely to have more sedentary time. There were sex differences in the association of area-level crime incidence with physical activity and sedentary behavior. These findings suggest that crime prevention should be considered when designing physical activity and sedentary behavior interventions for older adults.

BackgroundFew studies have investigated both the self-perceived and measured environment with objectively determined physical activity in older adults. Accordingly, the aim of this study was to examine measured and perceived environmental associations with physical activity of older adults residing across different neighborhood types.MethodsOne-hundred and forty-eight older individuals, mean age 64.3 ± 8.4, were randomly recruited from one of four neighborhoods that were pre-determined as either having high- or low walkable characteristics. Individual residences were geocoded and 200 m network buffers established. Both objective environment audit, and self-perceived environmental measures were collected, in conjunction with accelerometer derived physical activity behavior. Using both perceived and objective environment data, analysis consisted of a macro-level comparison of physical activity levels across neighborhood, and a micro-level analysis of individual environmental predictors of physical activity levels.ResultsIndividuals residing in high-walkable neighborhoods on average engaged in 11 min of moderate to vigorous physical activity per day more than individuals residing in low-walkable neighborhoods. Both measured access to non-residential destinations (b = .11, p < .001) and self-perceived access to non-residential uses (b = 2.89, p = .031) were significant predictors of time spent in moderate to vigorous physical activity. Other environmental variables significantly predicting components of physical activity behavior included presence of measured neighborhood crime signage (b = .4785, p = .031), measured street safety (b = 26.8, p = .006), and perceived neighborhood satisfaction (b = .5.8, p = .003).ConclusionsOlder adult residents who live in high-walkable neighborhoods, who have easy and close access to nonresidential destinations, have lower social dysfunction pertinent to crime, and generally perceive the neighborhood to a higher overall satisfaction are likely to engage in higher levels of physical activity behavior. Efforts aimed at promoting more walkable neighborhoods could influence activity levels in older adults.