Abstract
Introduction:
Limitations in physical function are predictive of adverse health outcomes, and screening has been recommended in clinical settings for older adults. Rarely assessed in community-based settings, physical function could provide insight for tailoring health-related community-based programs and raise awareness about this important aspect of health. This cross-sectional study seeks to demonstrate the feasibility of integrating physical function assessments into health screenings in African American churches in Chicago, IL through a large health partnership, and to determine the prevalence and correlates of physical function limitations among midlife (age 40–59 years) and late-life (age ≥60 years) participants.
Methods:
Screenings were held in 7 churches in Spring 2018. Physical function was assessed using the Short Physical Performance Battery. Demographics, medical history, health status, and health behaviors were assessed. Age-stratified logistic regression identified independent predictors of physical function limitations (score ≤9) among midlife and late-life participants (data analyzed in 2018–2019).
Results:
Among 731 participants, (median age=57 [IQR=51–65] years, 58% women, 97% African American), 25% of midlife and 56% of late-life participants had physical function limitations. For midlife participants, fair/poor health (OR=1.83, 95% CI=1.10, 3.05), stroke/neurologic conditions (OR=2.42, 95% CI=1.07, 5.46), and arthritis (OR=2.25, 95% CI=1.32, 3.81) were associated with higher odds of limitations. Fair/poor health (OR=1.97, 95% CI=1.11, 3.50) and stroke/neurologic conditions (OR=7.85, 95% CI=2.22, 27.74) were related to limitations among late-life participants.
Conclusions:
Physical function screening was successfully implemented into this large-scale church-based health screening program. Physical function limitations were prevalent, particularly at midlife; this information will be used to guide future programs.
INTRODUCTION
Physical function (PF) screening in clinical settings has been recommended to identify risk of adverse age-related outcomes.1 Despite its importance for healthy aging, PF is rarely assessed in community health screenings. Including PF in community screening could provide insight for tailoring health-related community-based programs and raise awareness about this important aspect of health. This study assesses whether PF can be incorporated into a health screening through churches in underserved African American communities in the West Side of Chicago, IL.2 It is hypothesized that: (1) PF can feasibly be assessed during the screening, (2) PF limitations are prevalent, and (3) correlates of PF limitations differ between midlife (age 40–59 years) and late-life adults (age ≥60 years).
METHODS
Health screenings were conducted in 7 predominantly African American churches in 2018 through a previously described academic–community partnership.2 Community partners suggested that PF limitations were common, a concern among residents, and should be assessed at the screening. Investigators and community partners determined that the Short Physical Performance Battery (SPPB)3 was acceptable for the setting and would be more enjoyable than a self-reported measure. Advisors assisted in solving the logistical aspects of PF screening in the churches, including providing suitable chairs and adequate testing space.
Study Sample
Overall, 1,106 congregants and community members took part in the screenings. This study focused on 731 participants aged ≥40 years who completed the PF assessment (86–130 participants per church) and had complete data on key correlates of PF (Appendix Figure 1). Rush University Medical Center IRB approved this study. All participants provided written informed consent.
Measures
The SPPB is a validated measure of lower extremity function comprising standing balance, 4-meter usual gait speed, and repeated chair stands.3,4 Scores range from 0 to 12 (0–4 points per subtask). Scores ≤9 indicate limitations, with standard cut points classifying mild (score 7–9), moderate (score 4–6) and severe limitations (score 0–3). Volunteer assessors were trained using publicly available tools.4,5 Informational materials on fall prevention were available for participants at the screening.
Age, sex, race, education (high school or less versus greater), general health status (excellent/very good/good versus fair/poor), smoking history, and physical activity guideline adherence (Stanford Leisure-Time Activity Categorical Item)6,7 were assessed via self-report. Chronic conditions were collected via questionnaire (self-reported clinician diagnosis of diabetes, hypertension, arthritis, asthma/lung disease, cardiovascular disease [heart attack/heart failure/circulatory problems], stroke/neurologic disease). Diabetes and hypertension were also defined using measured HbA1c >6.5% and blood pressure (≥130 mmHg systolic or ≥80 mmHg diastolic), assessed as part of the health screening. These were chosen based upon prior research on PF.8–11
Statistical Analysis
Statistical analyses were performed using SAS, version 9.4 in 2018–2019. Investigators compared characteristics between those with and without PF limitations, stratified by age group, using Mann–Whitney and chi-square tests. The age cut off of 60 years was utilized as average life expectancy is ≤70 years among African Americans in Chicago’s West Side.12 Independent associations with PF limitations were examined overall and stratified by age group. Models were selected using the least absolute shrinkage and select operator technique using the Schwarz Bayesian Criterion.
RESULTS
The PF measure was completed by 98% of screening participants aged ≥40 years. Various locations were utilized for testing, including hallways and multipurpose rooms. Participants wearing shoes restricting movement (like high heels) were given and encouraged to wear socks. There were no adverse events from PF screening.
Table 1 shows participants with and without PF limitations stratified by age group. Overall, 38% of participants had PF limitations, increasing among older ages (Figure 1). Among those with limitations, 76% had mild, 16% had moderate, and 8% had severe limitations. Age, fair/poor health, stroke/neurologic conditions, and arthritis were independently associated with PF limitations overall (Table 2).
Table 1.
Overall Participant Characteristics and Differences Between Limitation Categories Within Age Group
| Participant characteristics | All participants N=731 |
Midlife participants Age 40–59 years | Late-life participants Age ≥60 years | ||
|---|---|---|---|---|---|
| SPPB ≤9 N=107 |
SPPB≥10 N=316 |
SPPB ≤9 N=171 |
SPPB≥10 N=137 |
||
| Demographics | |||||
| Age, median (25th, 75th) | 57.0 (51.0, 65.0) | 54.0 (49.0, 56.0) | 52.0 (47.0, 56.0) | 70.0 (65.0, 74.0) | 64.0 (62.0, 69.0)*** |
| Female sex, n (%) | 425 (58.1) | 55 (51.4) | 164 (51.9) | 119 (69.6) | 87 (63.5) |
| African American race, n (%) | 706 (96.6) | 101 (94.4) | 299 (94.6) | 170 (99.4) | 136 (99.3) |
| Education ≤high school, n (%) | 366 (50.3) | 58 (54.2) | 148 (47.0) | 95 (55.6) | 65 (48.1) |
| Health factors | |||||
| Fair/Poor health, n (%) | 259 (35.8) | 52 (49.1) | 102 (32.6)* | 71 (42.0) | 34 (25.0)** |
| BMI, median (25th, 75th) | 30.3 (25.9, 36.2) | 29.9 (24.8, 35.8) | 31.0 (25.8, 37.4) | 30.5 (27.4, 36.4) | 29.0 (25.3, 33.3)* |
| Ever smoker | 442 (61.1) | 64 (60.4) | 190 (60.7) | 104 (61.5) | 84 (62.2) |
| Not meeting physical activity guidelines, n (%) | 531 (76.1) | 77 (77.0) | 222 (73.0) | 138 (85.2) | 94 (71.2)** |
| Chronic conditions | |||||
| Hypertension, n (%) | 530 (72.5) | 73 (68.2) | 201 (63.6) | 146 (85.4) | 110 (80.3) |
| Diabetes, n (%) | 224 (30.6) | 33 (30.8) | 67 (21.2)* | 73 (42.7) | 51 (37.2) |
| Stroke or neurologic condition, n (%) | 62 (8.5) | 16 (15.0) | 18 (5.7)** | 25 (14.6) | 3 (2.2)*** |
| Arthritis, n (%) | 309 (42.3) | 48 (44.9) | 82 (25.9)*** | 112 (65.5) | 67 (48.9)** |
| Asthma or lung disease, n (%) | 145 (19.8) | 27 (25.2) | 60 (19.0) | 39 (22.8) | 19 (13.9)* |
| Cardiovascular disease,a n (%) | 119 (16.3) | 21 (19.6) | 36 (11.4)* | 42 (24.0) | 21 (15.3) |
Note: Boldface indicates *<0.05 **<0.01 ***<0.001 when comparing between Short Physical Performance Battery (SPPB) ≤9 versus SPPB ≥10 within age group. Percentages calculated from participants with complete data for the variable, missing data <5% for all variables.
Combined heart failure, prior heart attack, or other circulation problems.
Figure 1.
Prevalence of physical function limitations (Short Physical Performance Battery [SPPB] score ≤9) by age group.
Table 2.
Logistic Models for Physical Function Limitations by Age Group
| Model parameter | Overall | Midlife participants Age 40–59 years | Late-life participants Age ≥60 years |
|---|---|---|---|
| OR (95% CI) | OR (95% CI) | OR (95% CI) | |
| Age (per year older) | 1.08 (1.06, 1.10) | 1.03 (0.99, 1.08) | 1.11 (1.06, 1.16) |
| Female | 0.98 (0.59, 1.65) | ||
| Education ≤high school | 1.51 (0.90, 2.55) | ||
| Fair/Poor health | 1.91 (1.34, 2.72) | 1.83 (1.10, 3.05) | 1.97 (1.11, 3.50) |
| BMI | 1.01 (0.99,1.03) | 0.98 (0.95, 1.01) | 1.03 (0.99, 1.07) |
| Smoking history | 0.58 (0.34, 1.01) | ||
| Not meeting physical activity guidelines | 2.67 (0.88, 3.19) | ||
| Hypertension | 0.84 (0.45, 1.56) | 0.54 (0.22, 1.32) | |
| Diabetes | 1.40 (0.80, 2.46) | ||
| Stroke or neurologic condition | 3.71 (2.02, 6.81) | 2.42 (1.07, 5.46) | 7.85 (2.22, 27.74) |
| Arthritis | 1.71 (1.19, 2.45) | 2.25 (1.32, 3.81) | 1.28 (0.74, 2.25) |
| Asthma or lung disease | 0.87 (0.47, 1.58) | 1.79 (0.86, 3.7) | |
| Cardiovascular disease | 1.30 (0.65, 2.61) |
Note: All variables from Table 1 considered in model selection. Though some relationship were not statistically significant, factors were retained as they improved overall model fit based upon model selection methods. Bolded relationships are statistically significant at p<0.05.
Among midlife participants, 25% had PF limitations with 82% of scores falling in the mild, 9% in moderate, and 8% in severe limitations categories. For the chair stand, gait speed, and standing balance subtasks, 68%, 24%, and 15% of participants, respectively, scored less than the maximum number of points. In logistic regression models for midlife participants, fair/poor health status, stroke/neurologic conditions, and arthritis were associated with higher odds of PF limitations (Table 2).
Among late-life participants, 55% had PF limitations, with 73% of scores falling in the mild, 11% in moderate, and 8% in severe limitations categories. For the chair stand, gait speed, and standing balance subtasks, 86%, 45%, and 36% of late-life participants scored less than the maximum number of points. In logistic regression models for late-life participants, age, fair/poor health status, and stroke/neurologic conditions were significantly related to higher odds of PF limitations (Table 2).
DISCUSSION
Acceptance of PF screening, easily adapted to space type and availability, was demonstrated by high participant completion rate (98%). Though the authors anticipated high prevalence of PF limitations among late-life participants (i.e., potentially >50%), the relatively high prevalence observed among midlife participants (25%) was surprising. Additionally, impairments in lower extremity muscle strength, based on lower-than-maximum scores for the chair stand measure, were observed for most participants in both age groups. Given the high risk of poor health outcomes associated with PF limitations,3,13 reducing these rates is imperative. Approximately 36% of participants reported fair/poor health—more than double the overall rate of fair/poor health in the surrounding county (17%),14—which was associated with limitations in both midlife and older adults. Arthritis was related to higher odds of limitations in midlife adults and could be a potential intervention target for this age group. Stroke/neurologic conditions were less prevalent, but overall participants reporting these conditions had 3.7-times higher odds of limitations than participants without these conditions, demonstrating how severely these conditions impact PF. As next steps, the team will conduct focus groups to understand community members’ perceptions of PF limitations and acceptability of intervention strategies to inform a new, community-based program aimed at improving PF among both midlife and older adults.
Though most studies of PF focus on adults in late life, the authors opted to include midlife participants as midlife is a crucial stage when limitations often emerge,15 particularly in conjunction with chronic conditions prevalent among this sample.16,17 Indeed the prevalence of PF limitations among the midlife participants was >12 times higher than prevalence reported in a similar age group using the SPPB,18 suggesting this age and community group is at high need for PF intervention.
Limitations
Limitations of this work should be considered. Participants were a self-selected sample of individuals physically able to go to a church. Those unable to attend church may have the most severe limitations but were not assessed. Most covariates were collected via self-report. The parent study was a needs assessment measuring a variety of potential health concerns, and not all potential correlates of PF limitations could be assessed in detail. Although volunteers were trained to administer the SPPB, training was not as robust as many research studies where assessors undergo rigorous training. Further, investigators were not able to bring the same chairs to each testing site. The chairs were similar but not identical, leading to slight variations between sites.
CONCLUSIONS
Screening for PF was successfully implemented into this large-scale church-based health screening program. PF limitations were prevalent, particularly at midlife, and this information will be used to guide future programs. This work can serve as a guide to investigators and community partnerships promoting healthy aging that may also benefit from assessing the functional status of their community members.
Supplementary Material
ACKNOWLEDGMENTS
We acknowledge and thank the pastors, church coordinators, and churches that participated in this study: Pastor Steve Epting, Kandice Jones, and Hope Community Church; Pastor Steve Spiller, Catherine Banks, and Greater Galilee Missionary Baptist (MB) Church; Pastor Marshall Hatch, Rochelle Sykes, Gigi Fuller, and New Mount Pilgrim MB Church; Pastor Cy Fields, Jessica Hudnall, and New Landmark MB Church; Pastor Ira Acree, Patty Ringo, and Greater St. John Bible Church; Pastor Floyd James, Sr., Precious James, and Greater Rock MB Church; and Pastor Michael Bryant, Tamara Gear, and Kedvale New Mt. Zion MB Church. Numerous volunteers from each church also helped conduct the health screenings. In addition, numerous volunteers and staff from Rush University Medical Center helped with the screenings, including Willie Mims, Serina Silvestry, and Shelby Gilyard.
Research reported in this publication was supported by National Heart, Lung, and Blood Institute of the NIH under Award Number R56HL135247. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. We would also like to thank Dr. David Ansell and Darlene Hightower and the Rush University Medical Center Department of Community Engagement for providing additional funding for this study. Funding was also provided by the Foglia Family Foundation and the Rush Center for Excellence in Aging. Study sponsors did not have any role in study design; collection, analysis, or interpretation of the data; writing the report; or deciding to submit the report for publication.
Footnotes
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Results from this study were presented in part at the Gerontological Society of America 2018 Annual Scientific Meeting, November 16, 2018, Boston, MA.
No financial disclosures were reported by the authors of this paper.
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