Journal of Gerontological Nursing

Research Brief 

Prevalence and Associated Factors of Physical Activity Among Older Adults Living in Nursing Homes: A Cross-Sectional Study

Lei Liu, MD; Huaping Liu, PhD; Mingqiang Xiang, MD; Hong Guo, PhD; Zhe Sun, MA; Tao Wu, MD


In many countries, the physical activity level of nursing home residents is low, and the amount of time spent on such behavior has not been quantified in China. In the current study, pedometers were used to measure the physical activity levels of 349 nursing home residents. Daily steps for residents ranged from 5 to 16,773 steps per day, with a median of 1,608 steps per day. Three hundred (85.96%) residents were sedentary, 16 (4.6%) were low active, and 33 (9.5%) were physically active. Factors such as the living conditions of the nursing home, younger age, lower body mass index, higher educational level, marriage, higher pension, and greater family support all led to a higher physical activity level among residents. Regarding sedentary level, male residents were more active than female residents. The physical activity level of nursing home residents in China is lower than the current World Health Organization standard. [Journal of Gerontological Nursing, 46(10), 19–26.]


In many countries, the physical activity level of nursing home residents is low, and the amount of time spent on such behavior has not been quantified in China. In the current study, pedometers were used to measure the physical activity levels of 349 nursing home residents. Daily steps for residents ranged from 5 to 16,773 steps per day, with a median of 1,608 steps per day. Three hundred (85.96%) residents were sedentary, 16 (4.6%) were low active, and 33 (9.5%) were physically active. Factors such as the living conditions of the nursing home, younger age, lower body mass index, higher educational level, marriage, higher pension, and greater family support all led to a higher physical activity level among residents. Regarding sedentary level, male residents were more active than female residents. The physical activity level of nursing home residents in China is lower than the current World Health Organization standard. [Journal of Gerontological Nursing, 46(10), 19–26.]

A high level of physical activity is associated with preservation of physical function, lower risk of chronic disease, and improved mood and cognitive condition (Frandin et al., 2016). Theou et al.'s (2011) systematic review found that physical activity can improve body composition, food intake, muscle function, upper and lower limb flexibility, and can lower depressive symptoms in older adults. Previous studies have shown that low physical activity level is related to high risk of cardiovascular disease, all-cause mortality, and cancer mortality, and higher physical activity level can reduce the risk of death (Demmer et al., 2017; Pettee et al., 2018; Sawada et al., 2014; Schmid et al., 2015). The recommended standard for physical activity in older adults (age >65 years) is 150 minutes of moderate aerobic exercise or at least 75 minutes of intensive physical activity every week, which can reduce the prevalence of vascular risk factors (Norton et al., 2014). Despite these findings, research in the United States, Australia, Canada, France, and Norway indicates that the physical activity levels of nursing home residents is low (Chen, 2010; de Souto Barreto et al., 2016; Egerton & Brauer, 2009; Kjøs & Havig, 2016; Nelson et al., 2007) and do not meet the recommended standard set by the World Health Organization (WHO) (Bates-Jensen et al., 2004).

Compared to community-dwelling older adults, nursing home residents face more obstacles in initiating and maintaining physical activity (Chen, 2010). It is hard for them to have a self-determined, active, and exciting life (Riedl et al., 2013). Nursing home residents spend most of their time sedentary after admission (Sackley et al., 2006), and some spend up to 94% of daytime hours sitting or lying down despite having the ability to be actively independent (MacRae et al., 1996). According to statistical data from the Ministry of Civil Affairs of the People's Republic of China (2017), the number of nursing homes in China increased from 38,000 to 116,000, and the number of nursing home beds increased from 1.533 million to 6.272 million between 2006 and 2015.

Although physical inactivity is a severe threat to public health, it has not been measured in nursing home residents in mainland China. Cognitive or memory impairment is a common characteristic in the older adult population, and it is difficult for many older adults to recall details of their daily activities (Hauer et al., 2011). An objective measurement method is needed to achieve more accuracy than the interviews or questionnaires currently used, which can be affected by memory bias (Resnick & Galik, 2007). Therefore, by measuring the physical activity level of nursing home residents, the current study explored the influence of sociodemographic factors, such as marital status, pension, and family communication, on the physical activity level of older adults.

In China, family values have a great impact on people. Physical activity level of nursing home residents will be greatly impacted by their level of family support. Thus, this study also conducted a survey of family support.

There were two objectives of the current study: (a) to describe the physical activity levels of nursing home residents in Beijing, and (b) to explore the factors associated with physical activity of nursing home residents in Beijing. This study was approved by the Ethics Research Committee of Peking Union Medical College. All study participants provided written informed consent.


Sampling and Study Design

A cross-sectional design was used to describe the physical activity level of nursing home residents in Beijing, China. A stratified sampling method was applied for investigating the physical activity of older adults age >60 years in five nursing homes at different levels. Nursing homes were ranked from 1 to 5 according to factors such as number of residents, building area, food service safety and sanitation, area for activities, the amount of fitness equipment, and nursing care level. The rating was classified according to the Classification and Evaluation of Old Age Institutions. Ranking was determined by experts from Beijing Star Rating Group to assess the star rating of nursing homes in Beijing. The higher the score, the higher the star rating, and thus, the better the nursing home.

There were 102 qualified nursing homes with 9,635 older adults in Beijing as of December 2016. Qualified older adult care institutions mainly include the following screening criteria: fire safety facilities up to standard, life safety facilities up to standard, staff safety awareness and professional literacy up to standard, and relevant personnel have certain emergency capacities. Of these 9,635 older adults, approximately 5,119 could walk unassisted; thus, a stratified sampling method was used to collect data from these older adults. Inclusion criteria were: (a) age ≥60 years, (b) living in a nursing home for at least 6 months, (c) walking unassisted, (d) having no moderate or severe cognitive impairment (Mini-Mental State Examination [MMSE] score ≥20) (Folstein et al., 1975), and (e) having the ability to communicate. Effective data and samples were selected with Microsoft® Excel and screened according to the inclusion criteria. After calculation, 400 residents in 86 nursing homes met the inclusion criteria.


Sociodemographic Information, Cognitive Function, and Anthropometry. Sociodemographic information, including age, gender, educational level, marital status, pension, body mass index (BMI), and family support, was collected using face-to-face interviews, with a self-designed questionnaire created by our project team. Family support mainly referred to the frequency of communication with family members, and the number of times per month a resident used the phone, video chat, or went home to visit relatives. Because the concept of familial piety is deeply rooted in Chinese culture, children in many families do not support older adults living in nursing homes (i.e., they tend to care for their older relatives at home), and their attitudes have a direct impact on the quality of life of older adults in nursing homes. If children encourage and support their relatives when they chat via phone or video, this outreach may increase older adults' happiness, thus potentially increasing their desire for physical activity. Family members can encourage or accompany older adults to perform physical activities, such as walking. Before data collection, the study team was trained on unified and standardized instructions for the interviews, such as how to control interview time, and checking questionnaire items when completed.

Cognitive functioning of participants was assessed by the MMSE (Folstein et al., 1975). The scale comprises nine aspects: time orientation, place orientation, immediate memory, delayed memory, attention, computation, sentence repetition, word fluency, and visual space. Total possible score is 30, where a score ≥24 indicates normal cognition, scores of 20 to 24 indicate mild impairment, scores of 10 to <20 indicate moderate impairment, and scores of ≤9 indicate severe impairment (Mungas, 1991).

Weight and body fat were measured using the Omron KARADA Scan Body Composition Scale (HBF-214-PK, Japan), which displays an individual's weight within an accuracy of 0.1 kg. Height was measured without shoes to the nearest 50 centimeters by a calibrated stadiometer. Height and weight were measured by the same ruler and weight scale. BMI was calculated using the following formula: weight (kg) divided by height squared (m2). In accordance with the WHO standard, BMI ≤18.5 kg/m2 indicates underweight, BMI ≤24.9 kg/m2 indicates normal weight, BMI ≥25 to 29.9 kg/m2 indicates overweight, and BMI ≥30 kg/m2 indicates obesity.

Physical Activity Level. Participants were asked to carry a pedometer while they were awake, except when swimming or bathing, throughout 7 consecutive days to monitor physical activity. Project team members instructed participants on how to use the pedometer.

The Omron HJ-302 pedometer has been used to measure daily step counts and assess physical activity level in many populations (Van Hoecke et al., 2014). The device is inexpensive and easy to carry, and features a single piezoelectric sensor with a 7-day memory for recall of daily step counts, aerobic step counts, calorie expenditure, and distance walked. Aerobic step counts refer to step counts that are >3 METs. A pedometer is an acceptable method to assess the daily steps of older adults (Cohen-Mansfield et al., 1997; Harris et al., 2009), and there is strong convergent validity between accelerometers and pedometers (R = 0.82, p < 0.001) (Floegel et al., 2016).

Data Reduction

To assess the physical activity level of participants, daily step counts were categorized into three levels: sedentary indicated walking <5,000 steps per day, low active indicated walking between 5,000 and 7,499 steps per day, and physically active indicated walking ≥7,500 steps per day (Tudor-Locke et al., 2013). Aerobic step counts could be ascertained from the pedometer when the walking speed of participants was >100 steps per 1 minute for a duration of 10 minutes successively. A pedometer is usually composed of a level gauge and a spring device that vibrates up and down when stepping. The electronic system connected by the device can accurately convert steps into digital signals. A duration of 30 minutes of moderate intensity physical activity as recommended by the WHO is equivalent to 3,000 aerobic steps per day for 5 days per week (Marshall et al., 2009).

Overall physical activity level was analyzed from data of step counts, aerobic step counts, calorie expenditure, and distance walked. Only valid data (i.e., data displayed on the pedometer) from participants who had ≥5 days of activity per week were used in the study.

Statistical Analysis

Each physical activity variable was expressed with descriptive and meaningful statistics, such as mean, median, and frequency. Some data were non-normally distributed and described by median and interquartile range, whereas normally distributed data were described by mean and standard deviation. Student's t tests were used to examine BMI. Two-tailed tests were used for all statistical procedures, with p < 0.05 indicating statistical significance. Statistical analysis was performed using SPSS 12.0.


Participant Characteristics

Among 400 participants who were eligible based on study criteria, 392 accepted interviews and 343 provided data of physical activity that were valid and included in the analysis. Sociodemographic characteristics of 343 participants by gender are shown in Table 1. Mean age of participants was 79 years, and most were ≥80 years old (male, 56.4%; female, 65.2%). In this sample, there were more females than males (male, n = 133; female, n = 210), and most participants had normal weight (male, 71.4%; female, 63.8%) and were single (male, 69.2%; female, 81%).

Characteristics of Participants by Gender

Table 1:

Characteristics of Participants by Gender

Pedometer Use

Among 400 participants, 55 (17.8%) participants did not wear the pedometer for ≥5 days. Five participants were hospitalized, three left the nursing home, and four misplaced the pedometer. Thus, 12 (3%) pedometers could not be retrieved.

Physical Activity Level

Overall physical activity level included mean values of daily step counts (1,719 [range = 449.5 to 3,685.9] steps), aerobic step counts (341 [range = 45.6 to 1,418.7] steps), calorie expenditure (18.6 [range = 2.3 to 59.3]), and distance walked (1.0 [range = 0.2 to 2.1] miles).

According to the classification standard of physical activity level, 78.2% of male participants were sedentary, 4.5% had low active status, and 17.3% were physically active. Similarly, 90.5% of female participants were sedentary, 4.8% had low active status, and 4.8% were physically active (Table 2).

Physical Activity Level of Participants

Table 2:

Physical Activity Level of Participants

Gender differences among the three levels of physical activity were analyzed. There was no difference in the low active and physically active levels based on gender. In the sedentary level, males were more active than females (p = 0.016) (Table 3).

Physical Activity Level of Participants by Gender

Table 3:

Physical Activity Level of Participants by Gender

Sociodemographic Factors of Physical Activity

Table 4 shows differences in sociodemographic factors of participants, such as ranking (i.e., nursing homes are rated on a scale of 1 to 5, with higher ratings indicating better comprehensive conditions [e.g., fitness facilities, amount of fitness equipment, human resource management]), gender, age, BMI, educational level, marital status, pension, and family communication. Physical activity level decreased as age increased (p = 0.001), males were more active than females (p < 0.001), older adults with obesity were more inactive (p = 0.001), and well-educated individuals were more active (p < 0.001). Married individuals were more active than unmarried individuals (p < 0.001). Older adults with higher pensions (p < 0.001) and persons receiving greater family support (p < 0.001) had higher levels of physical activity.

Sociodemographic Factors of Physical Activity in Older Adults

Table 4:

Sociodemographic Factors of Physical Activity in Older Adults


The physical activity level of nursing home residents was <3,000 aerobic steps per day for 5 days per week, which is the moderate intensity physical activity level recommended by the WHO (Marshall et al., 2009). Physical activity data showed that most older adults in nursing homes were sedentary (85.7%) or low active (4.7%). The mean values of daily step count and aerobic step count were 1,719 and 341, respectively, which not only indicate that most residents have low step counts, but also low intensity, such as transfer from bed to washroom or chair. A cross-sectional study from France (de Souto Barreto et al., 2015) indicated that although 35.4% of nursing home residents (1,914 of 5,402) distributed in 175 nursing homes participated in exercise classes, only 9% (487 of 5,402) were rated highly active. A cohort study from the United States (Bates-Jensen et al., 2004) showed that most nursing home residents spent at least 17 hours per day in bed. Xing (2014) collected data from Taiwan's Directorate General of Budget and stated that 80% of older adults age >65 were inactive. These findings show that nursing home residents currently have low physical activity levels.

In contrast, higher quality nursing homes usually provide larger activity areas and more sports facilities and exercise options. Therefore, residents of these facilities are more likely to participate in sports activities.

Previous studies indicated a decrease in physical activity with aging (Jefferis et al., 2015; Lohne-Seiler et al., 2014). With decreases in bodily function coupled with an increase in various chronic diseases, the mobility, balance, flexibility, muscle, and endurance of older adults diminishes (Spirduso et al., 2005). The same conclusion has been reached in the current study. This study also revealed a significant difference in the sedentary lifestyles of male and female participants, concluding that the physical activity level of males is higher than that of females. This is contradictory to the results of Barber et al. (2015), who found no significant difference between male and female residents in nursing homes, which may be related to educational level. Therefore, the current study further explored findings based on educational levels. Compared with females (17.1%), more males (41.4%) attained high school education or above, which agrees with previous research conducted in China (An et al., 2014; Fu et al., 2013). Older adults with a higher educational level have more access to information about activities through books, newspapers, or the internet, and thus are expected to be more physically active.

Lack of support from families was also seen as an impediment to physical activity in nursing home residents (Guerin et al., 2008; Resnick et al., 2008). In China, the concept of family is important, especially for older adults who are away from their families, and they may experience stress and loneliness living in a nursing home. Other factors also impacted physical activity level, such as pension. Higher pensions bring about higher levels of physical activity as they ensure access to sports facilities, exercise programs, or training courses, allowing older adults more opportunities for physical activity.

Nursing homes can help increase the physical activity of residents in two ways: one is simple housework, and the other is simple outdoor activity. Housework is considered low-level exercise, and it is based on principles of moderation and safety, and can include shopping, cooking, and cleaning. Nurses need to accompany older adults when they do housework to avoid falls and other hazards.

Limitations and Future Research

Although only older adults who could walk without assistance were selected for this study, measurement using the pedometer would have higher precision compared to merely using the questionnaire approach. However, a concern over the use of pedometers by older adults has been raised by some researchers (Crouter et al., 2003). One of those concerns is that pedometers can be used to measure step count but not intensity and therefore walking speed cannot be determined. Accelerometers measure the body's acceleration in one or more directions continuously for long periods. The output, activity counts per unit of time, calculated from the magnitude and the intensity of the acceleration, distinguishes between different walking speeds and intensity levels. In addition, in this exploratory experiment, other questions about the pedometer arose, such as whether the aerobic step count is accurate, and whether the aerobic step count really represents the day's moderate intensity exercise of participants. To answer these questions, further experiments are needed, such as using an actigraph, which can monitor the heart rates of individuals in real time, which can be used in combination with a pedometer.

Although a random sampling method was used, older adults who participated in this study all lived in Beijing. Therefore, the results are not generalizable to other populations. Such a narrow representation could be improved if the study were extended to other regions, such as smaller cities, towns, or villages in China. If carried out in this manner, the study would be able to represent a cross-section of nursing home residents in the entire country.


The physical activity levels of nursing home residents in China are far below the standard set by the WHO. Further research could focus on the barriers and interventions to increasing physical activity level and reducing sedentary behavior in nursing homes. Older residents and residents who lack support from their families had lower levels of physical activity. Lower levels of physical activity were also found in residents who did not possess a high level of education and had lower income (Pan et al., 2009). Therefore, interventions may need to be tailored for such groups to achieve more positive health outcomes despite these challenges.


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Characteristics of Participants by Gender

Variablen (%)
Overall (N = 343)Males (n = 133; 38.8%)Females (n = 210; 61.2%)
Age (years)
  60 to 6965 (19)34 (25.6)31 (14.8)
  70 to 7966 (19.2)24 (18)42 (20)
  ≥80212 (61.8)75 (56.4)137 (65.2)
Body mass index
  Underweight22 (6.4)7 (5.3)7.1 (15)
  Normal weight229 (66.8)95 (71.4)134 (63.8)
  Overweight88 (25.7)30 (22.6)58 (27.6)
  Obese4 (1.2)1 (0.8)3 (1.4)
Educational level
  Elementary school or lower144 (42)35 (26.3)109 (51.9)
  Junior high school87 (25.4)43 (32.3)44 (21)
  Senior high school54 (15.7)24 (18)30 (14.3)
  College or higher58 (16.9)31 (23.3)27 (12.9)
Marital status
  Single (unmarried, widowed, or divorced)262 (76.4)92 (69.2)170 (81)
  Married81 (23.6)41 (30.8)40 (19)
Pension (Yuan per month)
  ≤1,00046 (13.4)20 (15)26 (12.4)
  1,001 to 2,00090 (26.2)20 (15)70 (33.3)
  2,001 to 3,000132 (38.5)51 (38.3)81 (38.6)
  ≥3,00175 (21.9)42 (31.6)33 (15.7)
Length of residence (months) (mean, range)22 (12 to 48)24 (12 to 48)24 (12 to 51)

Physical Activity Level of Participants

Physical Activity Level (Steps Per Day)n (%)
Sedentary (<5,000)104 (78.2)190 (90.5)294 (85.7)
Low active (5,000 to 7,499)6 (4.5)10 (4.8)16 (4.7)
Physically active (≥7,500)23 (17.3)10 (4.8)33 (9.6)

Physical Activity Level of Participants by Gender

Physical Activity LevelMales, Median (IQR)Females, Median (IQR)Zp Value
Sedentary (<5,000 steps per day)1,761 (649 to 3,028)1,061 (303 to 2,469)−2.4180.016
Low active (5,000 to 7,499 steps per day)6,418 (5,634 to 7,072)6,152 (5,290 to 6,990)−0.7590.492
Physically active (≥7,500 steps per day)10,623 (8,511 to 12,979)9,112 (7,833 to 11,921)−1.5280.133

Sociodemographic Factors of Physical Activity in Older Adults

CharacteristicStep Counts, Median (IQR)p Value
  Male2,357 (1,020 to 4,795)
  Female1,251 (346 to 3,099)
Age (years)0.0038*
  60 to 693,113 (970 to 7,777)
  70 to 792,015 (816 to 4,353)
  ≥801,367 (369 to 2,885)
Body mass index0.0041*
  Underweight651 (214 to 2,208)
  Normal weight1,683 (433 to 3,701)
  Overweight1,909 (950 to 4,465)
  Obese304 (138 to 1,500)
Educational level0.0052*
  Elementary school or lower1,210 (245 to 2,471)
  Junior high school842 (2,413 to 4,716)
  Senior high school1,784 (485 to 4,133)
  College or higher2,699 (837 to 3,915)
Marital status0.0043*
  Married2,580 (1,491 to 4,314)
  Single (unmarried, widowed, or divorced)1,367 (381 to 3,494)
Pension (Yuan per month)0.0030*
  ≤1,0001297 (279 to 3,167)
  1,001 to 2,0001,587 (371 to 2,854)
  2,001 to 3,0001,558 (418 to 3,598)
  ≥3,0012,647 (1,023 to 4,358)
Family communication (interactions per month)0.0060*
  ≤1260 (95 to 640)
  2 to 42,093 (1,321 to 3,318)
  ≥56,952 (4,091 to 10,146)

Dr. L. Liu is PhD Candidate, and Dr. H. Liu is Professor, School of Nursing, Peking Union Medical College, Beijing, China; Dr. Xiang is Associate Professor, Department of Sports and Health, Guangzhou Sport University, Guangzhou, China; Dr. Guo is Professor, School of Nursing, Mr. Sun is Associate Professor, Department of Foreign Language, and Dr. Wu is Associate Professor, Department of Experimental Training Center, Shenyang Medical College, Shenyang, China.

The authors have disclosed no potential conflicts of interest, financial or otherwise.

The authors thank the Civil Affairs Bureau and the Nursing Home Association of Shenyang City for their assistance in supporting this research by providing information on nursing homes involved in this study. The authors also thank the School of Nursing, Peking Union Medical College for their assistance in acquiring pedometers and gifts for participants, and the School of Nursing, Shenyang Medical College for their assistance in printing questionnaires and data collection.

Address correspondence to Huaping Liu, PhD, Professor, School of Nursing, Peking Union Medical College, No. 33 Ba Dachu Road, Shijingshan District, 100144, Beijing, China; email:

Received: July 29, 2019
Accepted: March 16, 2020
Posted Online: July 08, 2020


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