Literature DB >> 34928997

Difference in predictors and barriers to arts and cultural engagement with age in the United States: A cross-sectional analysis using the Health and Retirement Study.

Meg Fluharty1, Elise Paul1, Jessica Bone1, Feifei Bu1, Jill Sonke2, Daisy Fancourt1.   

Abstract

INTRODUCTION: Arts and cultural engagement are associated with a range of mental and physical health benefits, including promoting heathy aging and lower incidence of age-related disabilities such as slower cognitive decline and slower progression of frailty. This suggests arts engagement constitutes health-promoting behaviour in older age. However, there are no large-scale studies examining how the predictors of arts engagement vary with age.
METHODS: Data from the Health and Retirement Study (2014) were used to identify sociodemographic, life satisfaction, social, and arts appreciation predictors of (1) frequency of arts engagement, (2) cultural attendance, (3) difficulty participating in the arts, and (4) being an interested non-attendee of cultural events. Logistic regression models were stratified by age groups [50-59, 60-69, ≥70] for the frequency of arts participation outcome and [50-69 vs ≥70] all other outcomes.
RESULTS: Findings indicated a number of age-related predictors of frequent arts engagement, including gender, educational attainment, wealth, dissatisfaction with aging, and instrumental activities of daily living (iADL). For cultural event attendance, lower interest in the arts predicted lack of engagement across age groups, whereas higher educational attainment and more frequent religious service attendance became predictors in older age groups (≥ 70). Adults in both age groups were less likely to report difficulties engaging in the arts if they had lower neighbourhood safety, whilst poor self-rated health and low arts appreciation also predicted reduced likelihood of this outcome, but only in the younger (50-69) age group. Adults in the older (≥ 70) age group were more likely to be interested non-attendees of cultural events if they had higher educational attainment and less likely if they lived in neighbourhoods with low levels of safety.
CONCLUSIONS: Our results suggest that certain factors become stronger predictors of arts and cultural engagement and barriers to engagement as people age. Further, there appear to be socioeconomic inequalities in engagement that may increase in older ages, with arts activities overall more accessible as individuals age compared to cultural engagement due to additional financial barriers and transportation barriers. Ensuring that these activities are accessible to people of all ages will allow older adults to benefit from the range of health outcomes gained from arts and cultural engagement.

Entities:  

Mesh:

Year:  2021        PMID: 34928997      PMCID: PMC8687585          DOI: 10.1371/journal.pone.0261532

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

A recent report by the World Health Organization found evidence that engaging in the arts has a range of health benefits, from supporting social determinants of health and playing a role in the prevention of mental and physical illness, to assisting in the management and treatment of various health conditions [1]. Arts engagement is a ubiquitous human behaviour that involves a number of ‘active ingredients’ that are known to be health promoting, including sensory activation, cognitive stimulation, a reduction in sedentary behaviours, and social interaction [1, 2]. These ingredients have been found to trigger a wide range of psychological, physiological, social and behavioural mechanisms that can, in turn, affect mental and physical health and health behaviours [3]. Specifically, there has been increasing research in recent years on the benefits of arts engagement in older age, with studies showing associations with reduced loneliness [4], lower incidence of depression [5], higher subjective wellbeing [6], slower cognitive decline [7], a lower risk of developing dementia [8], lower incidence of chronic pain [9], lower incidence of and slower progression of frailty [10], lower risk of developing age-related disability [11], lower incidence of chronic diseases such as cardiovascular disease and cancers [12], and lower mortality rates [13]. As such, arts engagement can be seen to constitute a health-promoting behaviour in older age. However, evidence from previous studies has suggested some age related barriers to arts participation (such as poor health, lack of time, and interest) and attendance of arts events (such as costs, no one to attend with, and lack of transportation) [14]. In the United Kingdom (UK) studies have shown noticeable declines in arts participation beginning around age 65 [14], with the steepest declines for individuals over 85 [14, 15]. Similar trends are seen with cultural attendance (such as visiting museums, historic parks and gardens) alongside declines in physical activity [16]. There have been reports of declining arts participation with age in the United States (US) as well [17-19]. Gender differences in engagement have also been observed, which may increase with age, with women in older age groups more likely to attend arts events than men [16]. A number of sociodemographic disparities in arts and cultural engagement have also been identified, which are often amplified in older age [14, 20]. These include illness and disability [21], living alone [21], lower educational attainment [21-23], ethnic minority status [24], and living in areas with high levels of poverty [16]. Therefore, it is important to understand how these previously identified sociodemographic disparities in access to the arts may change as people age. Additionally, it has been demonstrated that there is little evidence of predictors of arts and cultural engagement changing over time, with predictors in the 1990s showing very high levels of similarity to predictors in the 2010s [25]. However, it is currently unclear whether predictors of arts engagement vary as people age; in other words, whether certain demographic, socioeconomic, or health-related factors cause more barriers to engagement in later life compared to in middle age. Further, there has been little distinction in the past between the predictors of arts engagement vs predictors of wanting to engage in the arts but not being able to. This is a crucial distinction as it differentiates between a lack of interest or motivation vs a lack of capability or opportunity [26]. A social gradient associated with interested non-attendance in the arts has been observed, with a number of additional barriers to engagement such as finances, lack of time, and transportation difficulties [25]. But this research has focused exclusively on attending arts events (such as classical music or opera performances) rather than other types of arts engagement (such as participatory art, i.e. production of art versus attendance and appreciation) and looked across adulthood rather than at older age specifically [25]. Therefore, the current study used a large nationally representative cohort study of adults over fifty years of age in the US (the Health and Retirement Study [27]) to explore in much greater depth (i) how predictors of arts engagement differ across different age groups and (ii) the consistency between predictors of engagement amongst all participants compared to participants who specifically wanted to engage but reported facing barriers. We hypothesised that sociodemographic, life satisfaction, social, health, and interest in the arts related factors would aid in predicting (1) arts and cultural engagement as people across different age groups, and (2) barriers to arts and cultural engagement across different age groups. Overall, we hypothesised that better socioeconomic circumstances, higher life satisfaction, better social and health functioning, and increased interest in the arts would be associated with more arts engagement as people aged, while the opposite would be associated with increased barriers to the arts as people aged.

Methods

Participants

Participants were drawn from the Health and Retirement Study (HRS), a nationally representative study in the United States of over 37,000 individuals over the age of 50 [27]. The study was initiated by the National Institute on Aging (NIA) and conducted by the Institute for Social Research (ISR) at the University of Michigan to track the Baby Boom generation’s transition from work to retirement. The HRS covers a range of topics including income and wealth, health, cognition, use of healthcare services, work and retirement, and family [27]. The initial HRS cohort was interviewed for the first time in 1992 and followed-up every two years with data collection still ongoing. Over the years, five other studies were merged with the initial HRS cohort; Asset and Health Dynamics among the Oldest Old (AHEAD), the Children of the Depression (CODA), the War Babies, Early Baby Boomers (EBB), and Mid Baby Boomers (MBB) [27]. HRS replenishes the sample every six years with younger cohorts to ensure the data continues to provide a fully representative sample of individuals over the age of 50 in the United States; more details on study design are described elsewhere [27].

Sample

Included participants were required to have responded to the enhanced interview questions on arts activities in HRS at wave 12 and/or participated in the wave 12 Culture and Arts module. Two samples were derived from the total merged HRS cohort for the present study. First, of the total number of participants recruited by the start of wave 12 in the year 2014 (N = 35,364), there were 21,525 known or presumed alive (via correspondence or family notification). Of these, there were 18,747 participants (87.1% response rate) [28] who took part in the core survey where one of our four arts outcomes, frequency of arts engagement, was measured. Within each wave, a rotating random 50% subsample is invited for an enhanced interview (N = 9,459 in 2014), and following the interview a questionnaire is left for participants to complete and mail back to the study offices [29]. A total of 7,541 completed the questionnaire in 2014, and there were 7,523 participants who completed arts activities questions who thus formed our sample for frequency of arts engagement analyses. Second, a random subsample of 1,500 respondents in the core survey were invited to participate in the Culture and Arts module in this wave. Of the 1,500 respondents recruited, 1,496 participants (99.7%) took part. Of these, 1,465 (97.9%) had non-missing data on our other three outcomes. This became the sample for our analyses on difficulty participating in the arts, cultural attendance, and missed cultural events.

Outcome variables

We focused on four outcome variables: frequency of arts participation, cultural attendance, difficulty participating in the arts, and missed cultural events. All four prompted participants to focus on the past 12 months. Frequency of arts participation was created by asking participants ‘How often do you [do writing, bake or cook, sew or knit, read, do hobbies, participate in a community arts group]’ with responses of ‘several times a week,’ ‘once a week,’ ‘several times a month,’ ‘at least once a month,’ ‘not in the last month,’ and ‘never.’ The most frequent response across questions was chosen, and answers were collapsed into ‘weekly or more,’ and ‘less than weekly.’ Cultural attendance in the past 12 months was assessed by asking participants ‘In the past 12 months, did you go to a movie, art museum or gallery, crafts fair, or a live performance, such as a concert, play, or reading?’ with responses of ‘yes’ and ‘no.’ Difficulty participating in the arts was operationalised from responses to the statement ‘It is difficult for me to participate in the arts,’ with responses of ‘strongly agree,’ ‘agree,’ ‘neither agree or disagree,’ ‘disagree,’ ‘strongly disagree.’ These were collapsed into ‘neutral / disagree’ and ‘agree.’ Our missed cultural events variable was created by asking participants ‘In the last 12 months, was there an event of this type that you wanted to go to but did not,’ with responses of ‘yes’ or no’. All outcomes were collapsed to binary due to small sample sizes in alternative categorisations.

Predictor variables

We included eighteen predictor variables, framed as presented in the 2014 wave of the HRS survey instrument. Sociodemographic variables were: (1) gender [men, women], (2) race/ethnicity [choices were offered as White (White/ Caucasian), Black/African American, Other ethnicity (American Indian or Alaskan Native, Asian or Pacific Islander, Other)], participations were required to choose one category and could not report multiple ethnicities, (3) marital status [married, unmarried (separated/divorced, widowed, and never married)], (4) educational attainment [none, high school/GED, college/postgraduate], (5) self-reported neighbourhood safety [excellent/good, fair/poor], (6) employment status [employed, unemployed/inactive, retired], and (7) wealth [quartiles]: total of all assets. Life satisfaction variables were: (8) satisfaction with aging yes vs no] and (9) satisfaction with life [yes vs no]. Social variables were: (10) religious service attendance [none, monthly or less, weekly] and (11) frequency of seeing friends [yearly or less, monthly vs weekly]. Health factors included were: (12) depression [present vs not]: measured using an 8 item version of the Centre for Epidemiological Studies Depression Scale (CES-D) [30], with those scoring ≥4 categorised as having depression [31]. (13) smoking status [smoker, non-smoker]: created by collapsing ex-smokers into non-smokers, (14) self-rated health [good/excellent, fair/poor], (15) difficulties with ‘instrumental activities of daily living’ (iADLs) [none, difficulties with activities, unable to do activities]: created by collapsing responses to activities including using maps, preparing hot meals, shopping for groceries, making phone calls, taking medicines, and paying bills/ tracking expenses [32]. (16) long term conditions [yes, none]: by indicating the presence of a number of disorders including complications from stroke, diabetes, lung disease, cancer, heart conditions, or other medical conditions. (17) cognition score [quartiles]: word recall summary score [28]. Appreciation for the arts was measured with: (18) interest in the arts index score (Cronbach’s alpha = 0.95) which is a mean of seven statements on attitudes towards the arts including ‘the arts are important to me’, ‘I enjoy the arts’, ‘I don’t have any interest in the arts’, ‘the arts help me stay active and engaged’, ‘the arts help me socialise with family and friends’, ‘I like to take lessons or classes in the arts’, and ‘I feel a sense of appreciation for the arts’. Responses were rated on a scale from 1 (strongly agree) to 5 (strongly disagree). Higher scores reflect lower appreciation for the arts.

Statistical analysis

First, logistic regression models were used to examine associations between sociodemographic, life satisfaction, social, health, and appreciation for the arts factors with either arts and cultural engagement or barriers to engagement for each of our four outcomes: (1) frequency of arts participation, (2) cultural event attendance, (3) difficulties participating in the arts, and (4) interested non-attendees. For our frequency of arts participation outcome, we also included age as a predictor variable for the first analysis (as we had more than two age groups. Next, all models were rerun stratified by age group. We stratified by three age groups [50–59, 60–69, ≥70] for the frequency of arts participation outcome and then stratified by two age groups [50–69 vs ≥70] for cultural event attendance, difficulty participating in the arts, and interested non-attendee status. All analyses were weighted according to age, race/ethnicity, education, and state in the US population to account for unequal sampling [33]. Multiple imputation by chained equations (MICE) was conducted to address missing data in exposures, resulting in 50 imputed datasets. We included participants without missing information on outcome variables in the imputation model (see S1 Table for pattern of missingness in study variables). All analyses were preformed using Stata 16 [34].

Results

RQ1: Predictors of arts participation and cultural attendance

Arts participation

In the sample (N = 7,523) used to examine frequency of arts participation, 59.7% were women, 32.6% were educated to the college/postgraduate degree level, and 49.0% were retired. A majority (88.2%) reported weekly or more participation in the arts, and 11.8% reported less than weekly participation. Predictors for the total sample are shown in Table 1. In comparison to ages 50–59, the 70+ age group was most likely to participate at least weekly in arts (OR = 1.81; 95% CI = 1.24, 2.64) (Table 1).
Table 1

Age related differences in predictors of frequency of arts participation in the past 12 months from logistic regression models.

Frequency of arts participation
Total sample AAges ≤ 59 BAges 60–69 CAges ≥ 70 D
N = 7523N = 1827N = 2316N = 3380
OR95%CIPOR95%CIPOR95%CIPOR95%CIP
Age (Ref 50–59) --
60–691.310.951.790.096
70+ 1.81 1.24 2.64 0.002
Gender (Ref Female) --
 Male 0.51 0.40 0.66 <0.001 0.650.391.060.084 0.41 0.27 0.61 <0.001 0.44 0.31 0.64 <0.001
Race/Ethnicity (Ref White) --
 Black/African American0.910.671.230.5221.480.822.650.1910.820.481.410.4750.720.461.150.168
 Other ethnicity [including American Indian or Alaskan Native, Asian or Pacific Islander]0.900.601.340.6021.500.673.360.3230.770.411.440.415 0.51 0.28 0.92 0.026
Marital status (Ref Married) --
 Unmarried1.010.781.310.9341.140.691.890.6190.960.611.500.8490.920.631.350.673
Educational attainment (Ref None) --
 High School/ GED 1.74 1.29 2.35 <0.001 1.670.873.210.1261.140.651.990.658 2.30 1.57 3.35 <0.001
 College / postgraduate 3.02 1.97 4.64 <0.001 1.960.864.470.111 2.51 1.20 5.22 0.014 6.04 3.21 11.37 <0.001
Neighbourhood safety (Ref Good/excellent) --
 Fair/Poor1.160.831.610.3840.970.511.850.9181.210.702.100.4981.240.771.980.374
Employment status (Ref Employed) --
 Unemployed/ Inactive0.940.671.320.7280.950.561.610.8580.890.521.530.6810.510.231.110.088
 Retired1.010.741.370.9601.510.524.420.4531.000.651.540.9910.590.291.200.145
Wealth, quartiled (Ref Quartile 1) --
 Quartile 2 1.50 1.11 2.02 0.008 2.42 1.32 4.47 0.005 1.400.842.330.1991.100.731.660.649
 Quartile 3 1.52 1.09 2.14 0.015 1.640.833.230.152 1.95 1.05 3.60 0.034 1.230.791.930.360
 Quartile 4 1.81 1.20 2.74 0.005 2.040.854.920.1111.710.853.430.1331.530.882.680.135
Satisfied with ageing (Ref Yes) --
 No 1.43 1.07 1.91 0.016 0.790.431.460.452 2.11 1.28 3.48 0.003 1.66 1.11 2.48 0.013
Satisfied with Life (Ref Yes) --
 No0.990.761.290.9480.970.581.610.9050.820.511.320.4181.180.801.730.400
See friends (Ref Yearly/less) --
 Monthly1.110.801.540.5501.110.562.210.7681.030.611.750.9071.170.741.840.507
 Weekly 1.61 1.13 2.30 0.009 1.510.703.280.295 1.81 1.05 3.12 0.032 1.410.882.270.151
Attend religious services (Ref Yearly/Less) --
 Monthly1.020.761.360.9210.840.501.430.5191.460.922.320.1110.680.451.020.064
 Weekly1.270.941.720.1150.960.521.770.8861.260.762.090.3691.470.972.210.070
Depression CES-D (Ref None) --
 Present0.810.591.120.2030.620.341.140.1261.110.631.950.7110.750.491.160.197
Smoker --
 Yes1.040.691.560.8420.760.411.410.3831.040.571.890.8991.560.842.890.159
Self-rated health (Ref Good/excellent) --
 Fair/Poor1.090.831.430.5471.150.642.050.6491.180.721.930.5100.930.651.320.680
iADL (Ref None) --
 Difficulties with activities 0.74 0.56 0.97 0.032 0.880.471.670.7040.700.431.130.140 0.64 0.45 0.91 0.012
 Unable to do activities 0.31 0.17 0.55 <0.001 0.340.081.490.154 0.32 0.11 0.95 0.039 0.31 0.14 0.67 0.003
Long term conditions (Ref None) --
 Yes0.880.681.150.3560.880.551.420.5950.940.611.430.7600.790.511.220.284
Total cognition score, quartiled (Ref Quartile 1) --
 Quartile 21.250.931.680.1411.360.662.830.4071.340.792.270.2801.030.721.480.861
 Quartile 31.170.801.710.4140.970.422.220.9421.530.822.850.1771.030.591.830.910
 Quartile 4 1.68 1.09 2.61 0.020 1.610.663.940.2941.860.933.720.079 2.88 1.24 6.66 0.014
Arts index 0.63 0.44 0.89 0.009 0.61 0.37 0.99 0.047 0.61 0.38 1.00 0.048 0.65 0.45 0.94 0.024

Note. Dashes indicate reference category

Frequency of participation is: Weekly or more vs Less than weekly to participants ‘How often do you [do writing, bake or cook, sew or knit, read, do hobbies, participate in a community arts group]’

Column A shows the total sample with age as a predictor; Columns B-D show age stratified analyses.

Note. Dashes indicate reference category Frequency of participation is: Weekly or more vs Less than weekly to participants ‘How often do you [do writing, bake or cook, sew or knit, read, do hobbies, participate in a community arts group]’ Column A shows the total sample with age as a predictor; Columns B-D show age stratified analyses. When stratified by age, individuals aged 50–59 in the second lowest wealth quartile had a higher likelihood of weekly or more arts participation (Quartile 2: OR = 2.42; 95% CI = 1.32, 4.47) than those in the lower wealth quartile (Table 1). In adults aged 60–69, higher wealth (Q3: OR = 1.95; 95% CI = 1.05, 3.60) and seeing friends on a weekly basis (OR = 1.81; 95% CI = 1.05, 3.12) were associated with greater odds of participating weekly or more in the arts. Adults aged 70 and older in the highest cognition score quartile were more likely than those in the lowest quartile to participate in arts at least weekly (OR = 2.88; 95% CI = 1.24, 6.66). Those in both the 60–69 and 70+ age groups were more likely to participate at least weekly if they had higher educational attainment and were not satisfied with aging. They were also less likely to participate in the arts if they were men and were unable to do iADLs (and difficulties with iADLs if aged 70+). All ages who had less appreciation for the arts were less likely to participate in the arts. A sensitivity analysis stratified by two age groups to be comparable to the analyses with the other outcomes is available in S2 Table.

Cultural event attendance

In the sample (N = 1,465) used to examine attendance at cultural events, difficulty participating in the arts, and interested non attendees, 61.2% were women, 30.0% were educated to the college/postgraduate level, and 43.7% were retired. More than half (64.9%) reported attending a cultural event in the past 12 months, 38.4% reported difficulties participating in the arts, and 39.8% missed an event they otherwise wanted to attend. Predictors for the whole sample are shown in Table 2. There was no evidence that cultural event attendance differed with age. When stratified by age, those aged 50–69 in the second and higher wealth quartiles ([Q2: OR = 3.26 95%CI = 1.62, 6.53], [Q3: OR = 4.18; 95% CI = 1.90, 9.21], [Q4: OR = 3.74; 95% CI = 1.57, 8.91]), and higher cognition scores (OR = 2.24; 95% CI = 1.02, 4.88) were more likely to have attended a cultural event. While individuals aged 70 and over with higher educational attainment ([high school: OR = 2.21; 95% CI = 1.23; 3.99], [college/ postgraduate: OR = 5.53; 95% CI = 2.53, 12.12]) and more frequent religious service attendance ([Monthly: OR = 2.53; 59% CI = 1.39, 4.60], [Weekly: OR = 3.12; 95% CI = 1.62, 5.99]) were more likely to have attended. Lower scores on the arts appreciation index were associated with decreased likelihood of cultural event attendance in both age groups.
Table 2

Age related differences in predictors of cultural event attendance in the past 12 months from logistic regression models.

Cultural event attendance
Total sample AAges 50–69 BAges ≥ 70 C
N = 1465N = 862N = 603
OR 95%CI P OR 95%CI P OR 95%CI P
Gender (Ref Female) --
 Male0.830.571.210.3310.950.571.590.8500.730.421.260.254
Race/ethnicity (Ref White) --
 Black/African American1.160.681.970.5971.500.723.130.2850.760.351.670.495
 Other ethnicity [including American Indian or Alaskan Native, Asian or Pacific Islander]1.150.562.350.7020.950.412.170.8961.500.297.690.630
Marital status (Ref Married) --
 Unmarried0.760.531.100.1410.750.451.250.2650.940.551.610.819
Educational attainment (Ref None) --
 High School/ GED 1.76 1.09 2.84 0.020 1.320.602.910.494 2.21 1.23 3.99 0.008
 College / postgraduate 3.38 1.87 6.09 <0.001 2.400.985.860.055 5.53 2.53 12.12 <0.001
Neighbourhood safety (Ref Good/excellent) --
 Fair/Poor1.920.933.970.0782.380.955.940.0651.520.465.030.497
Employment status (Ref Employed) --
 Unemployed/ Inactive0.690.401.190.1850.780.381.570.4760.570.211.530.265
 Retired0.750.481.160.1950.680.361.300.2440.970.442.140.934
Wealth, quartiled (Ref Quartile 1) --
 Quartile 2 1.96 1.13 3.39 0.016 3.26 1.62 6.53 0.001 0.850.362.000.708
 Quartile 3 2.09 1.20 3.64 0.010 4.18 1.90 9.21 <0.001 0.960.412.240.920
 Quartile 4 2.31 1.24 4.29 0.008 3.74 1.57 8.91 0.003 1.350.553.340.517
Satisfied with aging (Ref Yes) --
 No1.190.632.230.5931.090.462.570.8401.260.503.190.627
Satisfied with Life (Ref Yes) --
 No0.790.401.560.4890.600.251.450.2561.210.473.110.686
See friends (Ref Yearly/less) --
 Monthly1.220.612.450.5761.310.533.250.5511.230.493.100.662
 Weekly1.450.623.420.3931.350.483.780.5681.680.505.620.393
Attend religious services (Ref Yearly/Less) --
 Monthly 1.70 1.11 2.62 0.015 1.360.752.490.312 2.53 1.39 4.60 0.002
 Weekly 1.58 1.01 2.48 0.046 1.070.572.010.828 3.12 1.62 5.99 0.001
Depression CES-D (Ref None) --
 Present0.820.461.480.5131.000.472.141.0000.540.221.310.173
Smoker --
 Yes0.820.481.400.4720.570.301.090.0881.680.594.780.332
Self-rated health (Ref Good/excellent) --
 Fair/Poor1.170.731.860.5181.280.672.450.4641.110.582.130.743
iADL (Ref None) --
 Difficulties with activities0.700.441.140.1500.740.371.480.3860.780.401.520.471
 Unable to do activities1.080.383.060.8923.310.9411.660.0620.450.121.750.249
Long term conditions (Ref None) --
 Yes0.820.551.200.2991.010.591.720.9810.660.371.160.147
Total cognition score, quartiled (Ref Quartile 1) --
 Quartile 21.340.872.060.1901.740.863.520.1251.060.611.860.828
 Quartile 3 2.03 1.19 3.47 0.009 2.24 1.02 4.88 0.044 1.790.853.780.127
 Quartile 4 2.29 1.28 4.11 0.006 2.200.984.930.0562.810.819.810.105
Arts index 0.36 0.27 0.48 <0.001 0.35 0.23 0.55 <0.001 0.34 0.23 0.50 <0.001

Note. Dashes indicate reference category.

Cultural event attendance is: yes vs no to ‘In the past 12 months, did you go to a movie, art museum or gallery, crafts fair, or a live performance, such as a concert, play, or reading?’

Column A shows total sample; Columns B-C show age stratified analyses

Note. Dashes indicate reference category. Cultural event attendance is: yes vs no to ‘In the past 12 months, did you go to a movie, art museum or gallery, crafts fair, or a live performance, such as a concert, play, or reading?’ Column A shows total sample; Columns B-C show age stratified analyses

RQ2: Predictors of barriers to arts engagement

Predictors of facing difficulty participating in the arts

Predictors for the whole sample are shown in Table 3. Age was not associated with facing difficulty participating in the arts. When stratified by age, those aged 50–69 who frequently attended religious services ([Monthly: OR = 2.78; 95% CI = 1.59, 4.85], [Weekly: OR = 2.12; 95% CI = 1.19, 3.77]) reported difficulties engaging in the arts, while low neighbourhood safety (OR = 0.37; 95% CI = 0.18, 0.75), poor self-rated health (OR = 0.52; 95% CI = 0.29, 0.96), and less appreciation for the arts (OR = 0.53, 95% CI = 0.38, 0.75) were associated with reduced likelihood of reporting difficulties engaging in the arts. While in those aged 70 and older, those in the third quartile of cognition (OR = 0.51, 95% CI = 0.28, 0,95) reported less difficulties engaging in the arts. Those in less safe neighbourhoods were less likely to report difficulties in engaging in the arts in both age groups, as were individuals of Black/ African American ethnicity.
Table 3

Age related differences in reported difficulties participating in the arts in the past 12 months from logistic regression models.

Difficulties participating in the arts
Total sample AAges 50–69 BAges ≥ 70 C
N = 1465N = 862N = 603
OR 95%CI P OR 95%CI P OR 95%CI P
Gender (Ref Female) --
 Male1.080.781.510.6481.240.781.960.3650.810.511.300.388
Race/Ethnicity (Ref White) --
 Black/African American 0.49 0.32 0.77 0.002 0.53 0.29 0.98 0.043 0.42 0.22 0.81 0.010
 Other ethnicity [including American Indian or Alaskan Native, Asian or Pacific Islander]0.820.461.460.5041.000.511.960.9940.680.202.340.542
Marital status (Ref Married) --
 Unmarried1.120.811.530.4950.980.621.550.9161.130.721.760.595
Educational attainment (Ref None) --
 High School/ GED1.320.862.020.2021.650.833.280.1491.200.722.020.486
 College / postgraduate0.650.391.100.1100.680.311.510.3470.700.361.360.290
Neighbourhood safety (Ref Good/excellent) --
 Fair/Poor 0.44 0.26 0.74 0.002 0.39 0.19 0.79 0.009 0.43 0.19 0.94 0.036
Employment status (Ref Employed) --
 Unemployed/ Inactive1.270.792.060.3301.190.642.210.5820.720.281.850.497
 Retired0.910.631.330.6330.840.491.440.5300.470.220.980.045
Wealth, quartiled (Ref Quartile 1) --
 Quartile 21.020.651.600.9220.930.511.690.8111.450.752.820.270
 Quartile 31.130.701.840.6201.190.602.350.6231.090.562.110.808
 Quartile 40.690.421.140.1500.610.301.240.1730.830.421.670.605
Satisfied with aging (Ref Yes) --
 No0.560.311.010.0550.550.261.180.1230.580.261.270.170
Satisfied with Life (Ref Yes) --
 No1.210.702.080.4891.380.672.840.3800.970.481.950.934
See friends (Ref Yearly/less) --
 Monthly1.000.561.800.9890.940.432.040.8671.060.442.550.891
 Weekly1.140.572.280.7041.120.462.690.8021.320.483.660.587
Attend religious services (Ref Yearly/Less) --
 Monthly 1.96 1.31 2.92 0.001 2.78 1.59 4.85 <0.001 1.220.712.110.470
 Weekly1.380.932.050.105 2.12 1.19 3.77 0.011 0.660.391.100.109
Depression CES-D (Ref None) --
 Present1.300.812.080.2721.830.993.380.0530.700.341.460.342
Smoker --
 Yes1.360.832.240.2211.730.923.240.0881.100.482.520.814
Self-rated health (Ref Good/excellent) --
 Fair/Poor0.690.451.050.081 0.52 0.29 0.96 0.036 0.930.531.630.792
iADL (Ref None) --
 Difficulties with activities1.280.831.970.2691.040.522.080.9021.360.802.290.254
 Unable to do activities0.440.161.250.1230.450.111.930.2810.320.071.470.144
Long term conditions (Ref None) --
 Yes 1.18 0.84 1.65 0.334 1.100.691.740.6961.250.772.020.365
Total cognition score, quartiled (Ref Quartile 1) --
 Quartile 21.130.751.690.5671.020.522.000.9581.340.822.180.238
 Quartile 3 0.58 0.36 0.95 0.030 0.660.311.390.269 0.51 0.28 0.95 0.033
 Quartile 40.660.401.080.0990.810.391.700.5830.480.221.030.058
Arts index 0.64 0.51 0.81 <0.001 0.53 0.38 0.75 <0.001 0.750.551.030.077

Note. Dashes indicate reference category.

Difficulties participating in the arts is: neutral/disagree vs agree to ’it is difficult for me to participate in the arts’

Column A presents the total sample; Columns B-C shows age stratified analyses

Note. Dashes indicate reference category. Difficulties participating in the arts is: neutral/disagree vs agree to ’it is difficult for me to participate in the arts’ Column A presents the total sample; Columns B-C shows age stratified analyses A sensitivity analysis was conducted by collapsing the outcome variable into ‘neutral/agree vs disagree’ (as opposed to neutral/disagree and agree) and is available in S3 Table. Results were largely the same with the addition that those with difficulties in iADLs were less likely to report difficulties participating in the arts.

Predictors of being an “interested non-attendee” at cultural events

Predictors for the whole sample are shown in Table 4. The odds of being an interested non-attendee did not differ in those aged 50–69 versus 70 and over. When stratified by age, individuals over 70 were more likely to be an interested non-attendee if they had higher educational attainment ([High School: OR = 2.32; 95% CI = 1.09, 4.93], [College/ postgraduate: OR = 3.40; 95% CI = 1.44, 8.00]), and less likely if their neighbourhoods were unsafe (OR = 0.33; 95% CI = 0.13, 0.81). Being in the highest quartile of cognition scores was the only other predictor of being an interested non-attendee in the 50–69 age group (OR = 2.35; 95% CI = 0.31, 0.60). Lower arts appreciation was consistently associated with lower likelihood of being an interested non-attendee in both age groups.
Table 4

Age related differences in predictors of interested non-attendees of cultural events in the past 12 months from logistic regression models.

Interested non attendees
Total sample AAges 50–69 BAges ≥ 70 C
N = 1465N = 862N = 603
OR 95%CI P OR 95%CI P OR 95%CI P
Gender (Ref Female) --
 Male1.130.811.580.4791.270.831.940.2710.730.421.290.279
Race/Ethnicity (Ref White) --
 Black/African American0.890.571.400.6200.840.491.440.5230.910.421.950.799
 Other ethnicity [including American Indian or Alaskan Native, Asian or Pacific Islander]0.620.341.110.1070.560.281.140.1080.940.332.690.908
Marital status (Ref Married) --
 Unmarried1.080.761.530.6751.130.711.810.6041.040.621.750.889
Educational attainment (Ref None) --
 High School/ GED 2.02 1.23 3.33 0.006 1.630.833.200.156 2.32 1.09 4.93 0.028
 College / postgraduate 2.52 1.42 4.47 0.002 1.900.884.080.100 3.40 1.44 8.00 0.005
Neighbourhood safety (Ref Good/excellent) --
 Fair/Poor0.690.381.260.2270.880.411.880.733 0.33 0.13 0.81 0.016
Employment status (Ref Employed) --
 Unemployed/ Inactive1.310.792.180.2971.170.632.170.6111.870.615.740.272
 Retired0.950.651.390.8050.950.571.590.8431.660.654.220.288
Wealth, quartiled (Ref Quartile 1) --
 Quartile 20.980.611.580.9260.780.431.410.4131.580.693.600.278
 Quartile 30.780.461.320.3550.670.341.330.2531.130.492.610.770
 Quartile 40.610.351.070.0830.500.241.060.0690.970.422.240.949
Satisfied with aging (Ref Yes) --
 No0.960.541.700.8871.020.512.060.9540.780.341.760.540
Satisfied with Life (Ref Yes) --
 No0.630.371.080.0930.630.321.240.1780.690.321.490.341
See friends (Ref Yearly/less) --
 Monthly1.460.772.780.2451.550.723.330.2661.300.433.920.641
 Weekly1.480.723.020.2821.570.683.610.2911.360.404.650.619
Attend religious services (Ref Yearly/Less) --
 Monthly0.930.621.410.7370.880.531.470.6200.930.471.830.836
 Weekly0.950.631.440.8180.800.461.380.4141.140.612.120.679
Depression CES-D (Ref None) --
 Present1.270.742.180.3811.490.752.950.2530.860.381.950.714
Smoker --
 Yes1.190.721.980.4920.970.531.790.9331.800.635.150.271
Self-rated health (Ref Good/excellent) --
 Fair/Poor0.890.561.410.6190.840.461.550.5841.240.652.370.519
iADL (Ref None) --
 Difficulties with activities1.350.862.130.1951.720.883.380.1151.120.622.020.698
 Unable to do activities1.520.514.500.4521.550.347.030.5731.520.327.240.597
Long term conditions (Ref None) --
 Yes0.990.691.400.9380.870.561.350.5361.650.922.960.093
Total cognition score, quartiled (Ref Quartile 1) --
 Quartile 21.340.852.120.2021.470.732.960.2761.100.621.980.743
 Quartile 31.200.702.050.5011.370.642.910.4180.790.391.580.503
 Quartile 4 2.03 1.20 3.42 0.008 2.35 1.10 5.02 0.027 1.170.562.450.678
Arts index 0.38 0.29 0.48 <0.001 0.43 0.31 0.60 <0.001 0.27 0.18 0.39 <0.001

Note. Dashes indicate reference category.

Interested non-attendees is yes vs no to ’In the last 12 months, was there an event of this type that you wanted to go to but did not’

Column A presents total sample; Columns B-C shows age stratified analyses

Note. Dashes indicate reference category. Interested non-attendees is yes vs no to ’In the last 12 months, was there an event of this type that you wanted to go to but did not’ Column A presents total sample; Columns B-C shows age stratified analyses

Discussion

Change in predictors of arts and cultural engagement across age

This study examined predictors of both arts and cultural engagement and barriers to engagement as people aged in the United States. For arts participation, only one factor, lower levels of interest in the arts, consistently predicted decreased likelihood of engagement across all three age groups. However, there was evidence that certain factors become predictors or became stronger predictors as people aged, such as gender, higher educational attainment, dissatisfaction with aging, difficulties with instrumental activities of daily living (iADLs), and cognition. Similarly, for cultural event attendance, lower interest in the arts predicted lack of engagement in both age groups, whereas higher educational attainment and more frequent religious service attendance became predictors as people aged. However, wealth became less important as a predictor of cultural event attendance with increasing age. Contrary to our hypothesis, some factors such as mental and physical health were not associated with either arts participation or cultural event attendance. When examining those who had expressed an interest in participating in the arts but faced barriers to doing so, those residing in areas with poor neighbourhood safety and individuals of Black/African American ethnicity, were associated with reduced likelihood of difficulties in both age groups. However, several factors predicted decreased likelihood of facing barriers to arts participation in the 50–69 age group only: lower arts appreciation, poor self-rated health, and religious service attendance. In the older age (70+) group, higher cognition predicted fewer barriers to arts participation. For cultural event attendance, adults with further educational attainment were more likely to be interested non-attendees, but only in the oldest age group (70+). Similarly, living in an unsafe neighbourhood predicted decreased likelihood of being an interested non-attendee in this age group, but not in the younger group. Having high levels of cognition predicted interested non-attendee status in the younger but not the older age group. Low arts appreciation was the only factor consistently associated with being an interested non-attendee in both age groups.

Demographic and health predictors

There is a broad literature showing that engagement with the arts has a range of physical, cognitive, and mental health promoting effects [1]. Our study found a number of demographic and health predictors of age-related arts participation, many of which such as gender and difficulty with iADL in older ages have previously been associated with reduced likelihood of engagement [7, 13, 14]. While there was no clear gradient for engagement across most age groups by race/ethnicity, those in the other ethnicity category (including American Indian or Alaskan Native, Asian or Pacific Islander) were less likely than white participants to participate in the arts in older ages, which might represent further socioeconomic barriers to attendance (i.e. inability to travel to a venue). Similar findings have been reported elsewhere [25], and the interconnectedness of race/ethnicity with further factors such as income and educational attainment (contributing to structural racism) should be taken into account [35]. However, we did find Black/African Americans were less likely to report barriers in arts engagement than those in other race/ethnicity groups.

Socioeconomic predictors

We also found that a number of socioeconomic predictors varied by whether they were related to arts or culture. Lower wealth was associated with arts participation in the youngest age group (50–59), while middle/average wealth was associated with increased likelihood of arts participation, but only in the 60–69 age group, while residing in unsafe neighbourhoods was associated with less difficulties participating in the arts. Conversely, higher wealth was associated with cultural attendance in the 50–69 age group. Similar general population findings have also identified these socioeconomic differences [15], which may suggest socioeconomic inequalities in older ages are greater for cultural attendance relative to arts engagement due to additional costs (e.g. tickets) and transportation required, while arts activities can more easily be undertaken at home and therefore potentially be more affordable. Future studies may wish to examine home-based cultural attendance activities (e.g., virtual museum tours) to identify if these differences are still observed; this may be of particular interest in light of the COVID-19 pandemic during which a large number of cultural activities have become digitalised. However, it is possible that digitalisation of these events could bring further age related inequalities among those with low digital literacy [36]. Additionally, education became an increasingly important predictor of participation and event attendance as people aged. This could also be an indication of cognitive capacity as adults with higher educational attainment are more likely to have better preserved cognition, which could enhance continued arts and cultural participation, which in turn is associated with better cognition [7, 37]. However, our measure of cognition was not consistently associated with participation or engagement, suggesting this does not fully explain the finding. So, this remains to be explored further.

Psychosocial predictors

We also examined a number of psychosocial predictors of engagement. Dissatisfaction with aging was a clear predictor for engagement with the arts for adults over the age of 60, which may support previous research showing that older adults (particularly following retirement) turn to the arts to aid with boredom, loneliness, and social connectedness [38, 39]. Arts and cultural appreciation are known to enhance social capital [40], however we found low levels of arts appreciation was a relatively consistent predictor of arts and cultural engagement across ages, suggesting it is an embedded predictor. Further, low appreciation for the arts was a constant predictor of not being an interested non-attendee and non-participant, reinforcing this concept. There was a difference observed in religious service attendance, with adults in the 70+ age group (but not the ages 50–69 group) frequently attending services reporting more frequent cultural event attendance. It is possible that the frequency of religious attendance increases social capital which in turn may encourage more community activity in a virtuous cycle [41]. Furthermore, some specific activities, such as live performances of singing, occur during some religious services and are often held in places of worship. Therefore, it is also possible that some older adults better retain the mobility and capacity to engage in community activities such as religious service attendance and cultural events, such that these activities correlate increasingly as people age. Unexpectedly, there were no patterns of association observed for depression status with engagement or barriers to engagement in arts and cultural events.

Implications

While there are already a number of known barriers to arts and cultural engagement, it is important to identify how these inequalities may continue to widen with age. Some factors identified may be multifaceted, such as race/ethnicity, which is interconnected with numerous socioeconomic factors (i.e. income and educational attainment) [35]. Additionally, there were barriers identified for cultural engagement which were not observed for the arts suggesting this may arise from additional social, financial, and transportation linked to attendance (as cultural engagement tends to be passive, i.e. museums, theatre etc.). Therefore, it is important to find ways to make cultural activities more accessible to people of all ages. For example, virtual theatres during the COVID-19 pandemic were able to reach wider audiences [42, 43]. Promoting these opportunities to older adults may help increase awareness and uptake if they continue to be digitalised. Adults who are isolated and lonely may avoid social situations for fear of vulnerability and further rejection [44]. Community outreach groups that are inclusive of all ages may be helpful to connect younger and older adults to attend these activities together [45-47]. Such community groups may also help overcome barriers such as transportation and costs (i.e., reduced group costing). Transportation barriers for older adults may be especially problematic in the US, primarily resulting from issues in built and social environment, transportation services, and individual attributes (e.g., a person’s ability to walk or rely on friends) [48], and research has repeatedly noted the need for accessible and affordable option for older adults [48-50]. Conversely, we found that there were fewer barriers for engagement with the arts, suggesting these activities are more likely once people can engage with at home, when alone, or that they may already be embedded within their regular cultural routines (i.e., singing for religious practices). Active arts activities, such as crafting or sewing, have been associated with longevity in older adults [13]. Increasing awareness of the range of health benefits associated with arts and cultural engagement is therefore important [1]. This can be done in the primary care settings, where for example, in the United Kingdom, social prescribing structures facilitate connecting people to community groups for arts activities, cookery, and gardening) [51].

Strengths and limitations

There are a number of strengths to the current study. HRS is large nationally representative cohort study of retirement and old age in the United States. The rich data collected in HRS on different aspects of aging (i.e., mental, physical, and cognitive) alongside the range of sociodemographic data available has allowed us to examine a number of potential predictors of age-related engagement with arts and cultural attendance. HRS has updated their variable choice and inclusive language across demographics since study inception. For example, increasing the number of race/ethnicity responses and allowing participants to choose more than one option, subsequently providing accurate choices to increase visibility of survey respondents and prevent social exclusionism through overgeneralisation into broad unrepresentative categories. Additionally, the 2014 Culture and Arts module provided a range of outcomes to examine, including both frequency of and difficulties in arts and cultural engagement. However, there are also a number of limitations to consider. The sample of individuals responding to the 2014 Culture and Arts module was small with respect to the total cohort sample, and therefore we were unable to stratify by more than two age groups. In doing so, we may have lost some variation by predictors between smaller age groupings. Similarly, we had to collapse some outcomes and predictors due to the small samples, for example we included ‘neutral’ with disagree when examining whether individuals reported difficulties engaging in the arts. However, we ran a sensitivity analysis including neutral along with agree and found results to be largely consistent with the current results with the additional inclusion of iADLs. Additionally, some survey questions were quite broadly phrased and are therefore difficult to make strong inferences from the data based on potential variation in interpretation across participations. For example, neighbourhood safety is based on a single self- reported question but we are unable to determine why participants may have felt unsafe (i.e. high levels of crime or lack of safe transportation options). Finally, these analyses were cross-sectional and therefore we cannot make causal inferences from the findings.

Conclusions

Our results suggest that socioeconomic inequalities in arts and cultural engagement may increase in older ages, with arts activities overall remaining more accessible (compared to cultural engagement). Given the numerous associations of arts and cultural engagement with mental and physical health outcomes in older age [11, 13, 37], reducing these inequalities is important to supporting health equity amongst older adults. The largest barriers to engagement we identified were for cultural engagement and likely involved transportation requirements. Therefore, this issue, along with upstream issues of structural racism and interconnected systems that embed inequities in systems and policies, must be explored further. Subsidized ticket prices for older adults and/or identification of how access to these events can be more home-based and offering accessible transportation are possibilities. Further, opportunities to increase awareness in primary care, such as social prescribing in the United Kingdom, has been proven beneficial in older adults [51]. Similar programs and policy, if adopted in the US, may aid in reducing age-related inequalities in access and ensure individuals of all ages are able to benefit from arts and cultural engagement and are encouraged as the focus of future research.

Missing data across arts outcomes.

(DOCX) Click here for additional data file.

Age related differences in predictors of frequency of arts participation- two age categories from logistic regression models.

(DOCX) Click here for additional data file.

Age related differences in reported difficulties participating in the arts- neutral/agree vs disagree from logistic regression models.

(DOCX) Click here for additional data file. 10 Aug 2021 PONE-D-21-14706 Difference in predictors and barriers to arts and cultural engagement with age in the United States: A cross-sectional analysis using the Health and Retirement Study PLOS ONE Dear Authors, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by 9 September 2021. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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As a researcher who focuses on the basic research of aging, it was great to read and learn about more wholistic contributors to the aging process and about potential impediments to aging individuals to take advantage of available option that can affect healthy aging. The article is well-written and thought provoking. However, there are a few minor adjustments that the authors should consider prior to publishing the article. 1. As PLOS ONE readers come from diverse backgrounds and areas of expertise, the authors should justify and explain the reasons for collapsing the responses which results in binary data (under methods -> Outcome variables) 2. The first discussion paragraph is simply a restatement of the results and does not add to the discussion. That is also somewhat true for the second discussion paragraph as well. In fact, the first sentence that provides critical assessment of the data comes only in the 7th sentence of the 3rd discussion paragraph. The authors should consider rewriting some of the discussion section to reflect a stronger critical assessment of the data and its relevancy to everyday life and health outcomes of aging individuals. Other than these two comments, I think that this short manuscript is a great addition to PLOS ONE and that many readers may find it useful. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: Yes: Arik Davidyan Ph.D. [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. 17 Sep 2021 We would like to thank the editors and reviewers for the opportunity to revise and resubmit, and for the helpful comments which have strengthen our manuscript. We have responded to each comment point-by-point below. Reviewer #1: This manuscript deals with a topic that is quite relevant in the current context. The introduction is well written, and I recommend that the authors insert the study's hypotheses at the end of the introduction. I also suggest that they provide a more robust justification for doing this work. Many thanks for the kind comments and are pleased you found this topic relevant and the writing clear. We have now added a sentence to more clearly introduce our study justifications, which are further outlined in paragraphs two and three of the introduction section. These justifications centre around the observation that while we know there are predictors of and barriers to arts and cultural engagement- there is little research on how these factors change as people age. Further, there has been little research into engagement versus wanting to engage (but being unable to do so) which this paper also examines. Further, we add to existing literature by examining predictors and barriers for different age groups of older adults, as well as active rather than passive arts engagement. We have also expanded the hypotheses to make this clearer. Regarding the method, I recommend that the authors insert the inclusion and exclusion criteria of the participants and the instruments used to identify the constructs. We have now included a statement in the methods to make clearer our process for selecting sample participants. This statement clearly states the inclusion criteria as well as a numeric breakdown of sample selection. If any validated instruments were used in the study (for example the CES- D or iADL), they were appropriately referenced. Therefore, the remaining variables were taken from questions which were available to us in the HRS survey and are summarised in the methods section. The data analysis should also be better described, presenting all the statistical procedures used in work. I recommend that the authors make a detailed description of the tables throughout the text. We have now updated the statistical analysis section and added text under each table to further clarify the statistical procedures used. The Discussion needs to be deepened, comparing the results found in this study with others in the literature. We have now expanded upon the discussion with additional references and comparisons to previous literature, relevance of the findings, and suggested policy implications. Reviewer #2: In this article, the authors provided interesting insights to predictors and barriers to participation and engagement with art and how these may change with aging. As a researcher who focuses on the basic research of aging, it was great to read and learn about more wholistic contributors to the aging process and about potential impediments to aging individuals to take advantage of available option that can affect healthy aging. The article is well-written and thought provoking. However, there are a few minor adjustments that the authors should consider prior to publishing the article. 1. As PLOS ONE readers come from diverse backgrounds and areas of expertise, the authors should justify and explain the reasons for collapsing the responses which results in binary data (under methods -> Outcome variables) We have now noted in our description of the outcome variables of the methods section that small sample size was the reason for our collapsing into binary categories. 2. The first discussion paragraph is simply a restatement of the results and does not add to the discussion. That is also somewhat true for the second discussion paragraph as well. In fact, the first sentence that provides critical assessment of the data comes only in the 7th sentence of the 3rd discussion paragraph. The authors should consider rewriting some of the discussion section to reflect a stronger critical assessment of the data and its relevancy to everyday life and health outcomes of aging individuals. We agree with the reviewers that a large portion of the discussion is focused on restating the results. However, as this study examined a large number of predictors and barriers to engagement across several outcomes, it is important these are summarised for our readers. To aid readability, we have now disaggregated these summaries and added subheadings. We have also extended the comparisons to previous literature and added text on the relevancy to life and health of ageing people. Other than these two comments, I think that this short manuscript is a great addition to PLOS ONE and that many readers may find it useful. Thank you for your kind comments about the manuscript, and we believe the new additions have further strengthened it. Submitted filename: Reviewer response letter_EP.docx Click here for additional data file. 6 Dec 2021 Difference in predictors and barriers to arts and cultural engagement with age in the United States: A cross-sectional analysis using the Health and Retirement Study PONE-D-21-14706R1 Dear Authors, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Marcel Pikhart Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: (No Response) ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No 9 Dec 2021 PONE-D-21-14706R1 Difference in predictors and barriers to arts and cultural engagement with age in the United States: A cross-sectional analysis using the Health and Retirement Study Dear Dr. Fluharty: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Marcel Pikhart Academic Editor PLOS ONE
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