Factors on Affecting Engagement of Physical Activity: Anderson Behaviour Model

doi:10.21203/rs.3.rs-5306155/v1

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Factors on Affecting Engagement of Physical Activity: Anderson Behaviour Model

https://doi.org/10.21203/rs.3.rs-5306155/v1

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Indonesia's national policy on non-communicable diseases focuses on modifying health behaviours. The implementation of this policy faces significant challenges, particularly in promoting physical activity. This study aims to examine factors influencing physical activity engagement, using three factors of the Anderson Behavioural Model as independent variables, while the dependent variable is engagement in the recommended 150 minutes of physical activity per week. Key factors associated with physical activity included age, awareness, and motivation to engage in physical activity. Lower engagement was observed in males, and Muslims. Enabling factors such as flexible work schedules, availability of public sports facilities, and community empowerment for communal physical activity also significantly influenced physical activity engagement. Need factors, including BMI and regular health check-ups, were not significantly associated. Strengthening the national NCD policy requires raising awareness of healthy living initiatives, providing accessible venues for physical activity, and empowering communities to engage in group activities.

physical activity

health policy

community engagement

non-communicable diseases

Lifestyle changes in the current era can lead to unhealthy habits, such as a sedentary lifestyle, which increases the risk of non-communicable diseases (NCDs) like diabetes, cardiovascular, and obesity [1]. NCD risk factors include metabolic, environment, and behaviour aspects with physical inactivity being a key modifiable factor, as the basis of the causes of NCD [2, 3]. However, global progress in increasing physical activity has been slow due to low awareness [4]. Globally, 25% of adults and 75% of adolescents fail to meet WHO’s recommended physical activity level. In Indonesia, low physical activity, particularly in Riau province, continues to rise, from 32.6% (2018) [5] to 41.2% (2023) [6], despite WHO’s goal to reduce inactivity by 10% [7].

Many factors influence community participation in physical activity, requiring both government and private sector involvement. Physical inactivity causes 9% of global death, and at least 30 minutes of moderate-intensity physical activity is recommended daily. Ethiopia has a monthly “car-free day” [8], whereas China promotes physical activity through its National Fitness Plan, encouraging cycling and walking [9]. Physical activity is categorized into light, moderate, and vigorous intensity [10, 11], with moderate physical activity, like fast walking or dancing, (3–6 METs) recommended for 150 minutes per week, or 75 minutes of vigorous physical activity, such as running or swimming, to reduce mortality [12, 13].

This study aimed to address the factors associated with people engagement of physical activity in Indonesia, particularly in Riau province. The findings are essential for developing the participation of community to implement the physical activity. The Anderson Behaviour Model serves as the framework for this study that consist of three domains. Firstly, predisposing factors are the factors influencing a people motivation or tendency to engage in physical activity, include demographic, knowledge, and attitudes towards health. Secondly, enabling factors are factors that determine whether an individual has the resources or environment that support physical activity, such as access to sports facilities, and leisure time. Lastly, need factors are the direct driving factors that make a person feel the need to engage physical activity, whether based on personal perception or medical evaluation.

Setting and Study Design

This cross-sectional study applied a cluster random sampling design, recruiting participants from 12 districts in Riau Province, Indonesia. It was conducted from February to September 2024, using an online self-reported questionnaire.

Participants’ Eligibility

The study involved adults aged 15–59 who had lived in Riau Province for at least six months. Participants were required to complete the questionnaire in the Indonesian language and have no significant barriers, such as difficulties recalling past information.

Variables
Variables were categorized according to the Anderson Behaviour Model, which includes predisposing, enabling, and need factors. The rationale for using this model was to assess engagement with government-proposed health interventions targeting risk behaviour modification. The study collected factors such as: Demographic factors: sex, age, marital status, religion, education, occupation, income, BMI, and district of residence. Health system factors: quality of public health services, access to health services, facilities, health staff services, health insurance, and health policy supporting physical activity. Individual and family factors: knowledge of physical activity, motivation for healthy behaviours, and family support. External factors: environmental influences such as health promotion, participation in health-related activities, and government or private support for public facilities.

Measurement Tools

The questionnaire was developed in Indonesian based on the Healthy Living Community Movement (Germas) program from the 2017 Presidential Instruction. It followed the WHO standard for physical activity (150 minutes per week). Content validity was tested using the Item-Objective Congruence (IOC), where a score of 0.5 or higher was considered acceptable. The questionnaire assessed the frequency and duration of physical activity over the past week. Those who performed 150 minutes or more were classified as meeting the physical activity standard, while those who performed less were considered below the standard.

Outcomes
The primary outcome was the engagement in recommended physical activity, as described above. Responses were recorded in binary format, indicating whether the participants met the standard within the last one month.

Sampling Technique and Sample Size

Sample size was calculated using the Design Effect due to the cluster random sampling approach across the 12 districts in Riau Province. The Design Effect was factored in to account for similarities among respondents within the same cluster. Using an assumed behaviour proportion of 31.9%, a type I error of 1.96, a margin of error of 3%, and a design effect factor of 1.55, the estimated total sample size required was 1,437. Accounting for a 10% dropout rate, a total sample of 1,577 participants was determined to be sufficient. The sample size per district was proportional to the population, so each district did not contribute the same number of participants.

Statistical Analysis

Descriptive analyses were performed on all variables, including normality tests for continuous data. Bivariate analysis was conducted to examine crude relationships between predictors and physical activity using logistic regression for categorical variables and independent t-tests (or non-parametric alternatives) for continuous data. The most influential factors were identified using binary logistic regression for variables with p-values less than 0.2 or those with plausible relationships to physical activity engagement. Adjusted odds ratios were calculated, along with 95% confidence intervals.

Ethical Approval

Informed consent was obtained from all participants, ensuring they understood the study’s purpose, benefits, and confidentiality measures, including de-identification. Participants could withdraw at any point. The study was approved by the ethics committee of the Faculty of Public Health, University of Hang Tuah Pekanbaru, Indonesia (approval number 016/KEPK/UHTP/II/2024), and a local recommendation letter was obtained from the Riau provincial government prior to data collection.

This study involved 1,577 participants, with 22% from Pekanbaru city and the rest from other districts. The average age was 36.5 years, and the largest age group was 35-39 years (18.3%). Most participants were female (59.73%), 52% had a bachelor’s degree, and 95% were Muslim. Additionally, 73.43% were married, and 66.4% (1,047 people) did not meet the recommended 150 minutes moderate physical activity (exercise) per week. Further details are provided in table 1.

Table 1. Percentage of Participants Characteristics

Variables		Frequency	%
Sex	Female	942	59,73
Sex	Male	635	40,27
Age	15-19	174	11.00
	20-24	105	6.70
	25-29	126	8.00
	30-34	211	13.40
	35-39	289	18.30
	40-44	265	16.80
	45-49	208	13.20
	50-54	126	8.00
	55-59	73	4.60
Marital status	Married	1158	73,43
	Single	376	23,84
	Divorced/widowed	43	2,73
Religion	Others	78	4,95
Religion	Islam	1499	95,05
Education	No formal education	4	0,25
	Primary school	56	3,55
	Junior High School	97	6,15
	Senior High School	371	23,53
	Diploma/Bachelor	820	52,00
	Postgraduate	229	14,52
Working hours	Fix Hours Working	910	57,70
	Non-Fix Hours Working	207	13,13
	Student	220	13,95
	Unemployed	240	15,22
Income per month (Provincial Minimum Wage)	< Rp. 3,300,000	734	46,54
Income per month (Provincial Minimum Wage)	≥ Rp. 3,300,000	843	53,46
BMI Range	Normal	133	8,43
	Underweight	443	28,09
	Overweight	315	19,97
	Obesities 1	482	30,56
	Obesities 2	204	12,94
Have you ever had the medical check-up regularly?	Never	325	20,61
	Yes, once a year	1039	65,88
	Yes, once 3 years	138	8,75
	Yes, once 5 years	75	4,76
Have you ever experienced difficulties accessing health services?	Never	1087	68,93
	Yes, I have	490	31,07
What do you think, are the health facilities in the area where you live complete enough?	Incomplete	585	37,10
	Complete	992	62,90
Do you have any health insurance from the government?	No	203	12,87
Do you have any health insurance from the government?	Yes	1374	87,13
According to what you know, are there any central or local government policies that implement a Healthy Living Community Movement?	No	730	46,29
	Yes	847	53,71
Did you know that engaging in regular exercise (physical activity) can help prevent disease and improve health?	No	15	0,95
	Yes	1562	99,05
Do you have the motivation to engage in regular exercise (physical activity)?	No	54	3,42
	Yes	1523	96,58
Do you have the motivation to eat healthy and nutritious food?	No	20	1,27
	Yes	1557	98,73
Do you have the motivation to not smoking?	No	42	2,66
Do you have the motivation to not smoking?	Yes	1535	97,34
Do you have the motivation to not drinking alcohol	No	18	1,14
Do you have the motivation to not drinking alcohol	Yes	1559	98,86
Do you drink alcohol?	No drinking alcohol	1557	98,73
Do you drink alcohol?	Yes	20	1,27
Do you smoke the cigarette?	Not smoking	1397	88,59
Do you smoke the cigarette?	Yes	180	11,41
Do you eat fruit and vegetables according to health standards, 5 types in 1 day?	Not Standard	1424	90,30
	standard	153	9,70
Physical activity (≥150 minutes a week for standard)	Not Standard	1047	66,40
Physical activity (≥150 minutes a week for standard)	standard	530	33,60
Do you know the Healthy Living Community Movement program related to physical activity?	No	1053	66,77
	Yes	524	33,23
Are you involved or participate in community sports activities around where you live?	No	976	61,89
	Yes	601	38,11
Are there any sports facilities provided at your workplace / school?	No	686	43,50
	Yes	891	56,50
Do you use mass public transportation, such as buses or trains, to go to work or school more often than using your own private vehicle, taxi, or online transportation?	No	1210	76,73
	Yes	367	23,27
Do you walk or cycle to work or school more often than using your own private vehicle?	No	1021	64,74
	Yes	556	35,26
Are there public facilities for sports or physical activities such as playgrounds around your residential area?	No	789	50,03
	Yes	788	49,97
Have you ever seen or heard an advertisement about clean and healthy living in your residential area?	Never	509	32,28
	Yes, I have	1068	67,72
Have you ever seen or heard an advertisement about clean and healthy living on applications or social media?	Never	372	23,59
	Yes, I have	1205	76,41
Have you ever attended as a participant in health education activities in your neighbourhood?	Never	748	47,43
	Yes, I have	829	52,57

Based on the Anderson Behaviour Model, factors influencing physical activity can be grouped into predisposing, enabling, and need factors. Predisposing factors include personal characteristics and motivations, with 96.58% of participants motivated to exercise, 98.73% to eat nutritious food, 97.34% to avoid smoking, and 98.86% to avoid alcohol.

Enabling factors involve external resources like income, employment, and access to healthcare. Over half (53.46%) earned above the provincial minimum wage, and 87.13% had government health insurance, though 31.07% faced healthcare access difficulties. Community sports participation was low (38.11%), only 35.26% walked or cycled to work or school, while 23.27% used public transportation.

Need factors include perceived health needs, 63.47% of participants were overweight or obese, and 99.05% recognized the benefits of regular physical activity. Awareness of health policies varied, with 53.71% familiar with the government’s Healthy Living Community Movement (Germas), and 52.57% had attended health education activities in their neighbourhood

The logistic regression analysis showed both significant and non-significant associations between various factors and the likelihood of engaging in recommended the physical activity. Details are in Table 2.

Table 2. Logistic regression model of related to physical activity

		B	Sig.	Exp(B)	95% C.I.for EXP(B)
		B	Sig.	Exp(B)	Lower	Upper
Sex	Female (ref)
Sex	Male	-0,315	0,025	0,730	0,553	0,962
Age	Age (year)	0,029	0,000	1,030	1,013	1,047
Marital status	Married (ref)		0,164
	Single	0,406	0,070	1,501	0,967	2,330
	Divorced/widowed	0,234	0,501	1,264	0,638	2,505
Religion	Others (ref)
Religion	Muslim	-0,671	0,016	0,511	0,296	0,883
District	Pekanbaru (ref)		0,371
	Dumai	-0,064	0,830	0,938	0,524	1,680
	Kampar	0,335	0,136	1,398	0,900	2,173
	Pelalawan	0,174	0,529	1,190	0,692	2,046
	Siak	0,326	0,191	1,385	0,850	2,257
	Kuansing	-0,092	0,758	0,912	0,508	1,637
	Bengkalis	0,417	0,078	1,517	0,955	2,412
	Kepulauan Meranti	0,307	0,374	1,359	0,691	2,672
	Indragiri Hulu	0,455	0,074	1,576	0,957	2,597
	Indragiri Hilir	-0,075	0,753	0,928	0,582	1,478
	Rokan Hulu	0,068	0,780	1,071	0,663	1,728
	Rokan Hilir	-0,143	0,565	0,866	0,531	1,412
Education	No formal education (ref)		0,177
	Primary School	20,236	0,999	614525751,128	0,000
	Junior High School	20,645	0,999	924823547,824	0,000
	Senior High School	20,180	0,999	580595827,643	0,000
	Diploma/Bachelor	20,571	0,999	858588106,107	0,000
	Postgraduate	20,335	0,999	678426808,523	0,000
Motivation to engage in regular exercise or physical activity	No (ref)
	Yes	1,296	0,009	3,653	1,382	9,656
Motivation to eat healthy and nutritious food	No (ref)
Motivation to eat healthy and nutritious food	Yes	0,366	0,634	1,442	0,320	6,494
Motivation to not smoking	No (ref)
Motivation to not smoking	Yes	0,126	0,787	1,134	0,455	2,826
Motivation to not drinking alcohol	No (ref)
Motivation to not drinking alcohol	Yes	-0,974	0,143	0,378	0,103	1,388
Eating fruit and vegetables according to health standards, 5 types in 1 day	Not Standard (ref)
	Standard	-0,022	0,915	0,978	0,657	1,457
Smoking the cigarette	Not smoking (ref)
Smoking the cigarette	Yes	-0,362	0,103	0,696	0,450	1,076
Drinking alcohol	No drinking alcohol (ref)
Drinking alcohol	Yes	-1,150	0,063	0,317	0,094	1,063
Knowing the Healthy Living Community Movement program related to physical activity	No (ref)
	Yes	0,371	0,003	1,450	1,135	1,852
Type of Working	Fix hours working (ref)		0,125
	Non fix/Flexible hours	-0,040	0,838	0,961	0,654	1,412
	Student	0,626	0,036	1,869	1,042	3,354
	Unemployed	0,305	0,186	1,356	0,864	2,129
Income per month	< Rp. 3,300,000 (ref)
Income per month	≥ Rp. 3,300,000	-0,053	0,705	0,949	0,722	1,246
Family support to participate in physical activity or exercise	(Never, Sometimes, Often)	0,025	0,832	1,026	0,810	1,298
The quality of health services at the public health centre or primary healthcare	(Very bad, Not Good, Quite good, Good, Very good)	-0,120	0,251	0,887	0,723	1,089
Difficulties access to the health services	Never (ref)
Difficulties access to the health services	Yes, I have	-0,174	0,219	0,840	0,636	1,109
The adequacy of healthcare services facilities in your area living	Incomplete (ref)
	Complete	-0,297	0,034	0,743	0,565	0,978
The quality of health staff during treatment	(Very bad, Not satisfied, Quite satisfied, Satisfied, Very satisfied)	0,099	0,337	1,104	0,902	1,351
Having health insurance from the government	No (ref)
Having health insurance from the government	Yes	-0,175	0,339	0,840	0,587	1,201
There are public facilities for sports or physical activities such as playgrounds around residential area	No (ref)
	Yes	0,287	0,019	1,333	1,048	1,695
More often walking or cycling to work or school than using own private vehicle	No (ref)
	Yes	-0,145	0,271	0,865	0,669	1,120
Using mass public transportation, such as buses or trains, to go to work or school more often than using own private vehicle, taxi, or online transportation	No (ref)
	Yes	-0,184	0,213	0,832	0,623	1,111
Sports facilities provided at workplace / school	No (ref)
Sports facilities provided at workplace / school	Yes	-0,085	0,498	0,919	0,719	1,174
Involved or participated in community sports activities around where people live	No (ref)
	Yes	0,491	0,000	1,634	1,271	2,101
Having seen or heard an advertisement about clean and healthy living in residential area	Never (ref)
	Yes, I have	0,169	0,292	1,185	0,864	1,624
Having seen or heard an advertisement about clean and healthy living on applications or social media	Never (ref)
	Yes, I have	0,283	0,111	1,328	0,937	1,882
BMI	Normal (ref)		0,366
	Underweight	0,310	0,220	1,364	0,831	2,239
	Overweight	0,390	0,151	1,477	0,867	2,515
	Obesities 1	0,201	0,453	1,222	0,724	2,064
	Obesities 2	0,068	0,817	1,070	0,604	1,895
The medical check-up regularly	Never (ref)		0,653
	Yes, once a year	0,191	0,303	1,211	0,841	1,742
	Yes, once 3 years	0,026	0,921	1,026	0,620	1,697
	Yes, once 5 years	0,052	0,869	1,054	0,566	1,960
Attending as a participant in health education activities in living area	Never (ref)
	Yes, I have	-0,140	0,284	0,869	0,673	1,123
Knowing that engaging in regular exercise (physical activity) can help prevent disease and improve health	No (ref)
	Yes	-0,314	0,600	0,731	0,227	2,357
People’ knowing whether there are central or local government policies on implementing Healthy Living Community Movement	No (ref)
	Yes	0,032	0,811	1,032	0,796	1,339
The type of health check-up	(Never health check-up, Basic health check-up, Comprehensive health check-up)	0,088	0,472	1,092	0,859	1,388

Sex significantly predicts physical activity, with males 27% less likely to engage compared to females. Age shows a 3% increased likelihood of engaging in physical activity per year of age. While singles are 50% more likely to be active than married individuals, this is not statistically significant. Religion influences physical activity, with Muslim 49% less likely to engage than others. Geographical effects are mixed, but Bengkalis and Indragiri Hulu residents show a potential higher likelihood of being active compared to those in Pekanbaru.

Motivation to engage in regular physical activity is a strong and significant predictor, making individuals over 3.5 times more likely to be active. However, motivation for healthy eating, not smoking, and not drinking alcohol do not significantly affect in physical activity levels. Awareness of the Healthy Living Community Movement (Germas) program increases physical activity likelihood by 45%, and access to public sports facilities, such as playgrounds, and community sports participation also boost activity.

While complete healthcare facilities reduce physical activity engagement by 26%, factors like Body Mass Index (BMI), income, having health insurance, and regular medical check-ups show no significant impact on physical activity. Workplace or school sports facilities are also not significant predictors of physical activity levels.

This study has divided three groups based on Anderson’s Behaviour Model, which are the followings.

Predisposing Factors

This study found that there were significantly decreasing more male than female by 27% to engage the standard time of physical activity. It is the same as another study that there is a higher proportion of women participate in physical activity than men because they have reasons related to appearance, health, and fitness [14].

It revealed a higher age-old people, a higher engaging standard of physical activity by 3% significantly. Previous study was in line with this finding, showing that today’s youth are less physically active compared to previous generations [15], and elderly people recognised the significance of engaging in sports and physical activity for mitigating the impacts of aging and fostering a social support network [16].

Furthermore, this study that single of marital status has 50% more participate than married status to carry out actively. Although, there is not significantly associated between divorced/widowed people to do physical activity compared to married status. Similarly to findings from another study, getting married did not lead to significant change in physical activity levels when compared to those who remained single [17]. Although, physical activity showed a notable decline after having a child, unlike in individuals who stayed child-less. It seems like they have less time to engage physical activity when they have more children to take care of them.

Another demographic is religion. This study revealed that Muslim people tended to decrease to carry out it compared to other religion. Some Muslims believe that the movements performed during prayer, outside of their religious significance, offer benefits to the circulatory, respiratory, digestive, nervous, and hormonal systems [18]. This is due to the fact that prayer is conducted at least five times a day, involving 40 rakaats (40 repetitions). These movements can be considered a form of stretching and isometric contraction exercise.

In addition, the knowing and motivation of people to implement physical activity have significantly to carry out the standard time of it. People who know about the Healthy Living Community Movement program, especially in regarding physical activity have significantly positive impact to engage physical activity by 45%. Therefore, this indicates that governmental efforts to raise public awareness about the importance of physical activity have been highly effective. Encouraging physical activity among sedentary adults recruited through primary care significantly boosted their activity levels over a 12-month period, as reported through self-assessment [19], it has been shown to be effective, with an additional 2.6 minutes of physical activity education leading to up to 283 minutes of physical activity per week. Therefore, it is important to expand the promotion of this government program and initiatives to larger community.

Furthermore, self-determined motivation was identified as a positive predictor of intentions to engage in physical activity during leisure time [20]. Similarly, individuals with motivation to engage in physical activity exhibited a significantly higher likelihood of meeting the specific time standards for physical activity participation. Intervention that affects health behaviour particularly using health belief model might be suitable to increase self-motivation and therefore should be recommended by policy maker or health provider.

On the other hand, there are not significantly associated between other factors to engage physical activity, such as education, district where they live, motivation to eat fruit and vegetables, to not smoking, and to not drinking alcohol. Another study stated no significant relationship between education and physical activity among men [21]. The research distinguished between educated men and women in its analysis. They further mentioned that men with lower education levels often engage in more physical demanding jobs, leading to higher occupational physical activity, which may result in similar total physical activity to men with higher education levels. In contrast, women with lower education levels are more likely to have sedentary jobs, making their occupational physical activity comparable to women with higher education levels.

It is also people living in among districts in Riau province, there are no relationship to engage physical activity compared to in capital city of Riau province (Pekanbaru). People who live in districts of Bengkalis and Indragiri Hulu are nearly significant positive 50% to its engagement. We assumed that Bengkalis and Indragiri Hulu, being rural areas, have greater access to open spaces and natural environments. Bengkalis has three separate big islands and has coastal areas near the sea, while Indragiri Hulu has a lake that serves as an open space. In contrast, Pekanbaru is an urban area with limited natural outdoor space and higher traffic congestion, as well as modern conveniences such as elevators, online transportation, and food delivery services. Contrary to another study [22], residents in rural areas were the least likely to meet the recommended physical activity level. Notable differences were observed across income groups and between urban and rural locations, particularly for those who identified neighbourhood streets, parks, and malls as their exercise spaces. Regarding other motivation in this finding, it is also contrary to another study that there were association between non-smoking and diet quality with physical activity engagement [23].

Enabling Factors

There are several enabling factors related to individuals’ resources, facilities and environmental supported that influence engagement in physical activity in this study. One key factor is the type of work particularly the working hours, which affects individuals’ available free time for physical activity. Although no significant relationship was found between work-hour flexibility and physical activity engagement, students were 87% more likely to engage in physical activity compared to those with fixed working hours. This could be due to more flexible schedules or access to sports facilities at school or universities. People working longer hours tend to feel more confident about engaging in physical activity when they have extended free time or flexible schedule, regardless of their sedentary behaviour [24]. This flexibility allows for better time management for physical activity compared to those with shorter working hours.

Infrastructure support from stakeholders, both governmental and private, has a significant impact in physical activity engagement among people. For instance, the presence of public sports or physical activity facilities in residential areas has been shown to have a notable effect. The availability of these facilities increases the likelihood of individuals engaging in physical activity, with those living in areas with access to public sports facilities being 33% more likely to participate in such activities. This suggests that the presence of public facilities can encourage individuals to be more active lifestyle. Additionally, another finding indicated that women aged 25-34 and 45-55 were significantly more likely to use local facilities compared to those aged 35-44 [25]. Higher levels of physical activity among these groups were also more strongly associated with the use of local facilities.

Additionally, community participation, regardless of size or ability, combined with mentor support and access to free or subsidized memberships, has positively impacted not only individuals' physical activity levels but also their physical and mental health [26]. Furthermore, these positive changes have extended to improvements in their families' lifestyles as well. This is further supported by the findings of this study that involvement in community sports activities around people live are significantly associated with a 63% increase in meeting the recommended standard for physical activity engagement.

This study also revealed that individuals residing in areas with comprehensive health facilities were 26% less likely to engage in physical activity. This result can be interpreted that the availability of sufficient health facilities may lead individuals to rely more on healthcare services rather than engaging in physical activity, indicating a preference for curative care over preventive measures such as physical activity. Physical activity is a proven method for both prevention and effective treatment in improving health [27]. Physical Activity Prescription (PAP) has been shown to increase patients’ activity levels, positively impact disease risk factors, and enhance quality of life. Therefore, physical activity should be an integral part of treatment within comprehensive health services and facilities.

Some other enabling factors were not associated with meeting the standard for physical activity engagement, including income, family support, difficulties in accessing the health services, and having health insurance. It was interpreted that having health insurance did not influence physical activity engagement, as individuals may feel confident that if they have a disease, they can rely on insurance to cover the healthcare services. Additionally, the findings indicated that monthly income did not significantly effect on physical activity engagement. This suggests that participation in physical activity may not be influenced by economic status. This implies that physical activity levels in Riau Province are not dependent on individual income. The proportion of people in Riau Province with incomes exceeding the Provincial Minimum Wage is higher than those with incomes below the standard (table 1).

Need Factors

These factors are influenced by personal perception or medical evaluation. Several Needs Factors indentified this study, including BMI, regular medical check-ups, participation in health-related activities, knowledge that engaging physical activity can help prevent diseases, awareness of government policies promoting the healthy living community movement, and the type of health check-up, did not significantly impact physical activity engagement. This includes individuals who are underweight, overweight, and obese compared to those with normal weight. Furthermore, People who regularly check their health status, whether annually, every three years, or every five years, with either basic or comprehensive medical check-ups, were not more likely to engage in the recommended levels of physical activity.

Strength and limitation

This study covers a larger area with a population of over 6 million people, encompassing various topographies and distinct lifestyle characteristics among participants. Additionally, we deployed a robust model that considers the health system as a key factor enabling engagement in the recommended physical activity. However, several limitations need to be addressed, including the inability to capture the longitudinal impact of these predictors on physical activity engagement. Furthermore, we acknowledge that the use of an online questionnaire may not reach the participants with low technology literacy, potentially affecting the generalisability of the study’s findings.

Based on the Anderson Behaviour Model, this study found that two factors (Predisposing and Enabling Factors) significantly influenced physical activity engagement in Riau Province, Indonesia. Predisposing factors include sex, age, religion, motivation and knowing to do physical activity. Additionally, enabling factors such as the adequacy of healthcare services facilities, being a student, the availability of public facilities that encourage physical activity, and involvement in community sports contributed to increased engagement in physical activity. On the other hand, none of the need factors were found to influence physical activity engagement.

One key point is that physical activity can be used both as a preventive measure and as a curative treatment to improve health status. It is not only preventive, but can also be prescribed as Physical Activity Prescription (PAP) for patients. Therefore, guidelines and models for the reimbursement of physical activity treatment costs in hospital settings are needed. Furthermore, national and international collaboration through networks to promote physical activity in healthcare settings can play a crucial role in the future.

These findings offer valuable insights for public health policymakers in developing more effective strategies to promote physical activity within communities, considering various influencing factors. This study highlights the importance of interventions that address demographic differences and individual health conditions to increase community engagement in physical activity, in accordance with the Anderson Behaviour Model theory.

NCD: Non-Communicable Disease

WHO: World Health Organization

BMI: Body Mass Index

PAP: Physical Activity Precsription

Conflicts of Interest:

On behalf of all authors declare that there is no conflict of interest.

Funding

There is not supported funding

Author Contribution

MB developed the proposal, analysed, interpreted data research, and wrote of the manuscript. KR reviewed and was responsible for the overall content as a guarantor, and ensured the work appropriately investigated and resolved. All authors contributed to read and approved the final manuscript

Acknowledgements:

We thank the Riau provincial government for the permission to collect data in Riau province and district government.

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No competing interests reported.

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Factors on Affecting Engagement of Physical Activity: Anderson Behaviour Model

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