HHS Public Access Author manuscript Author Manuscript
Asia Pac J Public Health. Author manuscript; available in PMC 2016 April 21. Published in final edited form as: Asia Pac J Public Health. 2016 January ; 28(1 Suppl): 53S–61S. doi:10.1177/1010539515598835.
Level of Physical Activity in Population Aged 16 to 65 Years in Rural Kerala, India O. P. Aslesh, MD1, P. Mayamol, MSW1, R. K. Suma, MD1, K. Usha, MD1, G. Sheeba, MSc(Nur)2, and A. K. Jayasree, MD1 1Academy
Author Manuscript
2College
of Medical Sciences, Kannur, Kerala, India
of Nursing, Pariyaram, Kannur, Kerala, India
Abstract
Author Manuscript
Kerala is a state in India with a high prevalence of cardiovascular diseases and diabetes. In order to control these diseases, the prevalence of modifiable risk factors such as low physical activity need to be studied. For this a cross-sectional study was conducted to assess the level of physical activity among 240 residents aged between 15 and 65 years in Kulappuram, a village in north Kerala. Low level of physical activity was seen in 65.8% of the study participants. The average duration of moderate to vigorous intensity physical activity per day in different domains such as work, travel, and recreation were 40.5, 10.1, and 12.7 minutes, respectively. The average duration of sedentary activities was 284.3 minutes per day. The level of physical activity was more among those engaged in unskilled work (adjusted odds ratio = 4.32; confidence interval = 1.38–13.51) and unmarried persons (adjusted odds ratio = 3.65; confidence interval = 1.25–10.65). No statistically significant difference in physical activity level was seen in different age, education, religious, and economic categories. The study concludes that the physical activity level was low in the study population.
Keywords noncommunicable diseases; epidemiology; population health; population studies; public health nutrition
Introduction Author Manuscript
Noncommunicable diseases such as cardiovascular diseases, cancer, and diabetes are the leading cause of morbidity and mortality around the world.1,2 Lack of physical activity is recognized as a major modifiable risk factor of these diseases.3,4 While considering the global burden of noncommunicable diseases, India contributes a major share.1 The state of Kerala has one of the highest prevalence of noncommunicable diseases in the country.5,6
Reprints and permissions: sagepub.com/journalsPermissions.nav Corresponding Author: P. Mayamol, Department of Community Medicine, Academy of Medical Sciences, Kannur 670503, Kerala, India. [email protected]. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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Lifestyle changes such as the adoption of unhealthy diet and physical inactivity are the major factors attributed to the rise in the noncommunicable diseases burden in the state.7 Over the past 2 decades, several studies had reported that the physical activity level among Indians was very low.8–11 The physical activity level in the state of Kerala was assessed using the Global Physical Activity Questionnaire as a part of the nationwide Noncommunicable Disease (NCD) Risk Factor Survey (STEPS—stepwise approach to surveillance) by the World Health Organization (WHO) and the Indian Council for Medical Research (ICMR) in 2003–2004 and 2007–2008. The 2 surveys showed marked difference in level of physical inactivity (5.9% in 2003–2004 and 74.5% in 2007–2008).12,13 Further research is needed to know whether this rise in level of physical inactivity is consistent over time.14 Hence, this study was undertaken to assess the prevalence of low physical activity level among adults aged 15 to 65 years in a village in northern Kerala.
Author Manuscript
Methodology A cross-sectional survey was carried out to assess the level of physical activity among residents of Kulappuram village, which comes under Cheruthazham panchayat in Kannur district, Kerala. The survey was carried out as a part of a health promotion initiative called Model Health Village project of the Community Medicine department Of our institute and Kulappuram Vayanashala, a local nongovernmental organization. The village had a total of 520 houses with 2206 residents in year 2012. The number of residents engaging in agriculture-related activity was less than 100. For the project, the village was divided into 20 clusters based on geography, and each cluster had 25 to 30 houses.
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For the study, a sample size of 240 was estimated after taking into account moderate to highlevel physical activity prevalence of 44% among South Indians as shown in the ICMR INDIAB study, relative precision of 20%, intended power of 80%, and design effect of 1.5.8 Out of the 20 clusters, 4 clusters were randomly selected by the lottery method and 60 individuals within each cluster were included in the study. Residents aged between 15 and 65 years were assessed for physical activity level. Those who were suffering from debilitating diseases or were physical challenged were excluded from the study. All the eligible members of a household in the selected clusters were assessed, and consecutive households were included in study till the required sample size was achieved.
Author Manuscript
The study was approved by Institute Ethical Committee of Academy of Medical Sciences, Pariyaram, Kannur, Kerala. The participants were interviewed after obtaining informed consent. The demographic and socioeconomic details of the participants were recorded using a questionnaire. The physical activity level was assessed using Global Physical Activity Questionnaire (GPAQ), which has been validated for Indian settings.15,16 The questionnaire in the local language has been used for the WHO-ICMR NCD risk factor survey (STEPS surveys) in the state.13 The GPAQ assesses self-reported duration and frequency of moderate to vigorous intensity physical activity during work, travel, and in recreation. It also assesses the time spent in sedentary activity.
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The data were entered in Microsoft excel and analyzed using EpiInfo7. As per the guidelines for interpreting GPAQ Version 2.0, individuals were classified as having low, moderate, or high level of physical activity. For this, the total time spent on physical activity during a typical week, the number of days in a week, as well as the intensity of physical activity were taken into account.16 The results were described in proportion, and χ2 test was used to test the significance of association between physical activity and sociodemographic variables. Binary logistic regression analyses (with all independent variables entered simultaneously) were subsequently undertaken to explore associations of the sociodemographic variables with physical activity level (high or moderate physical activity vs low physical activity). The mean duration per day of moderate to vigorous intensity physical activity (MVPA) in different domains as well as that of sedentary activity was estimated, and the differences across sociodemographic variables were tested by ANOVA (with post hoc analysis using Tukey test). Multiple linear regression was executed to identify significance of association of sociodemographic variables with the dependent variables: overall MVPA, work MVPA, recreation MVPA, transport MVPA, and sedentary activity. Sociodemographic variables considered were age (continuous), gender, occupation (3 categories), education (2 categories), marital status (2 categories), type of family (2 categories), income (2 categories), religion (2 categories), and chronic illness (2 categories). Statistical significance was set at . 05.
Author Manuscript Results
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Among the 240 study participants, 128 (53.3%) were females and 112 (46.7%) were males. The participants in the younger age groups (15–25 years) constituted 25.4% of the total, and the older age group (56–65 years) constituted 18.3%. About half of the participants (45%) were educated at the high school level or more. Majority (70.8%) of the study participants were Hindus. Only 29.6% of the participants belonged to the below the poverty line group as per the ration card details Table 1).
Author Manuscript
In the study, it was found that 65.8% of the participants had low level of physical activity. High level of physical activity was found among 17.9% of the participants, and moderate level of physical activity was seen among 16.3% of the participants. In the logistic regression analysis, it was seen that the level of physical activity was more among those engaged in unskilled work (adjusted odds ratio [OR] = 4.32; confidence interval [CI] = 1.38–13.51) when compared with unemployed/retired persons. Also, higher physical activity level was seen among unmarried persons (adjusted OR = 3.65; CI = 1.25–10.65) when compared with ever married. No statistically significant association of physical activity level was seen with different age group, education, religion, family type, presence of chronic diseases, and economic categories. Overall, the mean time spent in MVPA was found to be 63.4 (standard error [SE] = 7.8) minutes/day (Table 2). The average time of MVPA during work, travel, and recreation was 40.5 (SE 7.8), 10.1 (SE 1.9), and 12.7 (SE 1.9) minutes/day, respectively. The mean duration per day of MVPA across different sociodemographic variables is given in Table 2. Multiple linear regression analysis shows that there is significant association of overall MVPA with occupation (B −44.6, P value .001), marital status (B −81.1, P value .002), and religion (B
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24.9, P value.03) (constant 284.2). Work-related MVPA was significantly associated with occupation (B −41.3, P value.001) and marital status (B −55.1, P value.013) (constant 196.3). Significant association was also found in recreational MVPA with gender (B −8.6, P value .02) and marital status (B −16, P value .01) (constant 19.8). The mean duration of sedentary activity among the study participants was 284.3 minutes per day. The duration of sedentary activity was similar across different age groups, gender, and other sociodemographic variables. The study shows that 75.6% of the study participants had no work-related MVI physical activity. The absence of recreational MVPA was seen in 86.2% of the study participants, and it was more common in females (92.2%) when compared with males (71.4%; P .004).
Discussion Author Manuscript Author Manuscript
The study shows that the majority (65.3%) of the study population had low level of physical activity. Over the past 2 decades, studies assessing the level of physical activity using the GPAQ in different parts of India had shown varied results. The STEPS survey conducted in 2003–2005 showed that physical inactivity was prevalent in 5.9% of the population in rural Kerala.12 However, the STEPS survey in 2007–2008 showed that low level of physical activity was seen in 74.5% of the rural population in Kerala, which was similar to the present study.12 In the STEPS survey 2007–2008, Kerala reported a higher level of physical inactivity when compared to the rural population in neighboring states of Tamil Nadu (61.6%) and Andhra Pradesh (63.8%). The ICMR-INDIAB study showed that low level of physical activity was seen in 55.4% of the rural population in Tamil Nadu.8 In a multisite cross-sectional study done in 2005, the prevalence of physical inactivity in rural India was 53%.9 The level of physical inactivity in the present study was far higher than the global estimate (31.1%) and that for the Southeast Asian region (17%).17 The high level of physical inactivity in the state may be the result of higher education status of its population as a result of which more and more people are preferring non-agriculture or less labor intense jobs.18
Author Manuscript
When different domains of physical activity was compared in the study, duration of workrelated physical activity was more when compared with that of recreational- or travel-related physical activity. The average minutes spent per day in MVPA during work was very low in the present study (40.5 minutes/day) when compared with the results the STEPS survey 2007–2008 for rural Kerala (161 minutes/day). This difference may be explained by the fact that only 14% of the study sample was involved in unskilled occupation, which requires intense physical activity, while in the STEP survey, 20% of the sample were involved in such work. In the study, three fourths of the population had no work-related MVPA despite this being a rural population. Decrease in work-related physical activity needed to be compensated by increase recreational physical activity to meet the WHO guidelines of 150 minutes of moderate to vigorous physical activity per week. But the present study shows that the average recreational MVPA was only 10 minutes/day, lower than the STEPS survey for rural Kerala (15 minutes/day). Recreation MVPA was absent in 86.7% of the study participants in the present study. This was similar to the results from the INDIAB study, which reported lack of recreational MVPA among more than 90% of the rural population in India. The present study reported a low level of recreational MVPA among females when
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compared with males. Several studies conducted in India reported similar finding and this can be due to cultural factors in the country, which restrict the participation of women in outdoor sports.8,13,19 Several studies show that age group, gender, urban living, religion, education, and occupation can be associated with physical activity level.8,20 In the present study, only occupation category (unskilled job vs unemployed/retired) and marital status (unmarried over ever married) were the factors that were significantly associated with physical activity level.
Author Manuscript
There are some limitations for this study. Since the study was using the GPAQ as an assessment tool, problems with self-reporting like overreporting or underreporting of physical activity cannot be ruled out. Also, many activities described in the GPAQ may not be culturally specific or relevant. Since the GPAQ counts only those activities done for a minimum duration of 10 minutes, many activities such as household work of housewifes may not be taken into account. Another limitation was that the sample size calculation was powered to detect the prevalence of moderate to high physical activity level and not for establishing association with any variable. Hence, the study was not able identify significant factors associated with physical inactivity.
Conclusion
Author Manuscript
The study shows that level of physical activity among the rural population of Kerala was alarmingly low. To reduce the burden of noncommunicable disease in the state, there is an urgent need to improve the overall physical activity level. As more sections of the rural population are getting employed in sedentary occupation categories, there is a need to promote recreational physical activities. This should begin early in life, at the school level, so that such activities become part of their lifestyle.
Acknowledgments Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: PM is supported by the ASCEND program which is funded by the Fogarty International Center at the United States’ National Institutes of Health (NIH), under Award Number D43TW008332 (ASCEND Research Network). The contents of this report are solely the responsibility of the authors, and do not necessarily represent the official views of the National Institutes of Health.
References Author Manuscript
1. World Health Organization. Global Status Report on Noncommunicable Diseases 2014. Geneva, Switzerland: World Health Organization; 2014. 2. Ramahi TM. Cardiovascular disease in the Asia Middle East region: global trends and local implications. Asia Pac J Public Health. 2010; 22(3 suppl):83S–89S. [PubMed: 20566538] 3. Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. 2012; 380:219–229. [PubMed: 22818936] 4. Li Y, Sato Y, Yamaguchi N. Lifestyle factors as predictors of general cardiovascular disease: use for early self-screening. Asia Pac J Public Health. 2014; 26:414–424. [PubMed: 22156564]
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5. Mohan V, Pradeepa R. Epidemiology of diabetes in different regions of India. Health Administrator. 2009; 22(1):1–18. 6. Raman Kutty V, Balakrishnan K, Jayasree A, Thomas J. Prevalence of coronary heart disease in the rural population of Thiruvananthapuram district, Kerala, India. Int J Cardiol. 1993; 39:59–70. [PubMed: 8407009] 7. Sivasankaran S, Thankappan KR. Prevention of non-communicable diseases requires a life course approach: a case study from Kerala. Indian J Med Res. 2013; 137:874–877. [PubMed: 23760370] 8. Anjana RM, Pradeepa R, Das AK, et al. Physical activity and inactivity patterns in India—results from the ICMR-INDIAB study (Phase-1) [ICMR-INDIAB-5]. Int J Behav Nutr Phys Act. 2014; 11:26. [PubMed: 24571915] 9. Ng N, Hakimi M, Van Minh H, et al. Prevalence of physical inactivity in nine rural INDEPTH Health and Demographic Surveillance Systems in five Asian countries. Glob Health Action. 2009; 2 10. Krishnan A, Shah B, Lal V, Shukla DK, Paul E, Kapoor SK. Prevalence of risk factors for noncommunicable disease in a rural area of Faridabad district of Haryana. Indian J Public Health. 2008; 52:117–124. [PubMed: 19189832] 11. Sugathan TN, Soman CR, Sankaranarayanan K. Behavioural risk factors for non-communicable diseases among adults in Kerala, India. Indian J Med Res. 2008; 127:555–563. [PubMed: 18765874] 12. Division of Non-communicable Diseases, Indian Council of Medical Research. Development of Sentinel Health Monitoring Centers for Surveillance of Risk Factors of Noncommunicable Diseases in India (April 2003 to March 2005): Collated Results of 6 Centers. New Delhi, India: Indian Council of Medical Research; 2005. 13. National Institute of Medical Statistics, Indian Council of Medical Research. IDSP NonCommunicable Disease Risk Factors Survey, Phase-I States of India, 2007-08. New Delhi, India: National Institute of Medical Statistics and Division of Non-Communicable Diseases, Indian Council of Medical Research; http://www.icmr.nic.in/final/IDSP-NCDReports/ Phase-1StatesofIndia.pdf. Published 2009 [Accessed February 17, 2015] 14. Ranasinghe CD, Ranasinghe P, Jayawardena R, Misra A. Physical activity patterns among SouthAsian adults: a systematic review. Int J Behav Nutr Phys Act. 2013; 10:116. [PubMed: 24119682] 15. Bull FC, Maslin TS, Armstrong T. Global physical activity questionnaire (GPAQ): nine country reliability and validity study. J Phys Act Health. 2009; 6:790–804. [PubMed: 20101923] 16. World Health Organization. Global Physical Activity Questionnaire—Analysis guide. http:// www.who.int/chp/steps/resources/GPAQ_Analysis_Guide.pdf. 17. Hallal PC, Andersen LB, Bull FC, et al. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet. 2012; 380:247–257. [PubMed: 22818937] 18. Office of Registrar General. [Accessed June 29, 2015] Executive Summary: Kerala Census. http:// www.censusindia.gov.in/2011census/PCA/PCA_Highlights/pca_highlights_file/kerala/ Exeutive_Summary.pdf 19. Kinra S, Bowen LJ, Lyngdoh T, et al. Sociodemographic patterning of non-communicable disease risk factors in rural India: a cross sectional study. BMJ. 2010; 341:c4974. [PubMed: 20876148] 20. Katulanda P, Jayawardena R, Ranasinghe P, Rezvi Sheriff MH, Matthews DR. Physical activity patterns and correlates among adults from a developing country: the Sri Lanka Diabetes and Cardiovascular Study. Public Health Nutr. 2013; 16:1684–1692. [PubMed: 22995708]
Author Manuscript Asia Pac J Public Health. Author manuscript; available in PMC 2016 April 21.
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Asia Pac J Public Health. Author manuscript; available in PMC 2016 April 21. 10 72
No illness
60
Chronic illness
22
Below poverty line
64
Above poverty line
18
Joint
11
Nuclear
40.0
16
Muslim Christian
36.0
25.0
35.5
31.0
33.3
37.5
36.7
32.4
42.6
31.3
42.0
27.3
35.4
32.7
48.6
32.1
31
38.6
34.7
29.5
33.3
34.4
%
55
26
Unmarried Hindu
56
47
Male Ever married
35
46
High school Female
36
17
Unskilled jobs Higher secondary or above
43
17
56–65 22
17
46–55
Unemployed, retired
13
Skilled: clerical, business, professionals, housewife, semiprofessionals
14
36–45
21
n
26–35
15–25
Abbreviations: OR, odds ratio; CI, confidence interval.
Chronic illness
Economic class
Type of family
Religion
Marital status
Gender
Education
Occupation
Age group
Categories
Moderate or High Physical Activity
128
30
109
49
128
30
19
24
115
35
123
65
93
84
74
18
91
49
27
32
31
28
40
n
64.0
75.0
64.5
69.0
66.7
62.5
63.3
60.0
67.6
57.4
68.7
58.0
72.7
64.6
67.3
51.4
67.9
69
61.4
65.3
70.5
66.7
65.6
%
Low Physical Activity
Author Manuscript
Level of Physical Activity Across Different Subgroups of the Study Sample.
.2
.5
.6
.6
.1
.02
.6
.15
.9
P Value
2.35
1.35
0.79
1.43
1.55
3.65
1.57
1.18
2.47
4.32
2.90
1.42
1.10
1.00
Adjusted OR
0.94–5.86
0.67–2.70
0.38–1.65
0.6–3.37
0.69–3.48
1.25–10.65
0.87–2.83
0.59–2.39
0.94–6.48
1.38–13.51
0.79–10.68
0.36–5.64
0.30–4.02
0.31–3.21
95% CI
Author Manuscript
Table 1 Aslesh et al. Page 7
Author Manuscript
Author Manuscript
Author Manuscript 27.2 34.4 66.9 54.4
26–35
36–45
46–55
56–65
30.5
Female
38.3 15.0
Skilled: clerical, business, professionals, housewife, semiprofessionals
Unemployed, retired
22.2
Higher secondary or above
Asia Pac J Public Health. Author manuscript; available in PMC 2016 April 21. 41.9
Ever married
70.9
Christian
Nuclear
40.8
16.7
Muslim
Type of family
40.7
Hindu
Religion
36.3
Unmarried
Marital status
55.9
High school
Education
100.4
Unskilled
Occupation
51.8
Male
Gender
22.6
15–25
Age group
Mean
7.4
28.5
9.0
7.6
8.2
10.7
6.4
10.9
5.9
8.4
28.7
8.7
10.3
17.7
20.1
15.3
11.5
8.9
SE
.9
.1
.7
.01
.001b
.1
.4
Work-Related MVPA Duration
9.2
8.2
24
7.0
5.1
24.4
15.1
5.7
17.0
7.7
4.4
5.0
15.9
7.2
1.1
8.4
11.2
19.6
Mean
2.1
4.1
7.3
1.9
1.4
5.9
3.4
2.0
4.8
2.0
3.7
1.7
3.5
3.5
0.7
3.7
4.2
5.7
SE
.4
.004d
.001
.02
.05
.004
.02a
Recreation-Related MVPA Duration
13.9
24.3
13.4
10.5
11.2
17.0
12.4
12.9
13.1
10.4
20.7
10.1
15.7
10.4
16.8
9.1
8.2
16.7
Mean
2.2
8.1
4.6
1.9
2.0
4.3
2.4
2.5
3.6
2.2
5.8
2.2
3.1
3.9
4.6
3.9
3.3
4.3
SE
.2
.05
.2
.9
.2
.1
0.4
Travel-Related MVPA Duration
63.9
103.5
54.1
58.2
58.2
77.8
49.7
74.5
45.1
56.4
125.6
45.5
83.3
72.5
84.8
51.9
46.6
58.9
Mean
8.8
30.1
13.8
9.1
8.9
16.3
9.5
11.8
10.6
9.4
31.7
9.4
12.6
18.5
21.7
16.8
14.7
14.9
SE
.8
.1e
.3
.1
.003c
.01
.5
Overall MVPA Duration
Mean Duration (in Minutes per Day) of Moderate to Vigorous Intensity Physical Activity (MVPA) at Work, Recreation, and Travel Among the Study Participants Across Different Sociodemographic Variables.
Author Manuscript
Table 2 Aslesh et al. Page 8
Author Manuscript 40.5
All
6.8
6.7
21.8
.2
10.1
2.1
11.6
11.5
9.3
1.9
1.6
2.2
4.0
2.1
4.3
SE
.07
.6
12.7
8.2
13.6
10.7
13.6
8.0
Mean
1.9
3.0
2.1
3.5
2.2
3.4
SE
.2
.5
63.2
66.8
62.4
73.5
58.8
60.3
Significant difference in transport-related physical activity duration (P < .05) between Hindus and Christians.
Significant difference in recreational physical activity duration (P < .05) between Hindus and Muslims.
7.8
22.6
8.3
17.4
8.4
17.0
SE
.8
.4
Overall MVPA Duration Mean
Significant difference in total physical activity duration between unskilled and skilled/business/clerical group as well as between unskilled and unemployed/retired.
d
e
56.4
Chronic illness
.3
13.0
Mean
Travel-Related MVPA Duration
Significant difference in work-related physical activity duration between unskilled and skilled/business/clerical group as well as between unskilled and unemployed/retired.
b
c
37.3
No illness
14.9
7.2
15.2
SE
Significant difference in recreational physical activity duration (P < .05) between age group 15–25 years and 46–55 years.
a
51.4
Below poverty line
Chronic illness
35.9
39.2
Mean
Above poverty line
Economic class
Author Manuscript Joint
Author Manuscript Recreation-Related MVPA Duration
Author Manuscript
Work-Related MVPA Duration
Aslesh et al. Page 9
Asia Pac J Public Health. Author manuscript; available in PMC 2016 April 21.
Asia Pac J Public Health. Author manuscript; available in PMC 2016 April 21. Published in final edited form as: Asia Pac J Public Health. 2016 January ; 28(1 Suppl): 53S–61S. doi:10.1177/1010539515598835.
Level of Physical Activity in Population Aged 16 to 65 Years in Rural Kerala, India O. P. Aslesh, MD1, P. Mayamol, MSW1, R. K. Suma, MD1, K. Usha, MD1, G. Sheeba, MSc(Nur)2, and A. K. Jayasree, MD1 1Academy
Author Manuscript
2College
of Medical Sciences, Kannur, Kerala, India
of Nursing, Pariyaram, Kannur, Kerala, India
Abstract
Author Manuscript
Kerala is a state in India with a high prevalence of cardiovascular diseases and diabetes. In order to control these diseases, the prevalence of modifiable risk factors such as low physical activity need to be studied. For this a cross-sectional study was conducted to assess the level of physical activity among 240 residents aged between 15 and 65 years in Kulappuram, a village in north Kerala. Low level of physical activity was seen in 65.8% of the study participants. The average duration of moderate to vigorous intensity physical activity per day in different domains such as work, travel, and recreation were 40.5, 10.1, and 12.7 minutes, respectively. The average duration of sedentary activities was 284.3 minutes per day. The level of physical activity was more among those engaged in unskilled work (adjusted odds ratio = 4.32; confidence interval = 1.38–13.51) and unmarried persons (adjusted odds ratio = 3.65; confidence interval = 1.25–10.65). No statistically significant difference in physical activity level was seen in different age, education, religious, and economic categories. The study concludes that the physical activity level was low in the study population.
Keywords noncommunicable diseases; epidemiology; population health; population studies; public health nutrition
Introduction Author Manuscript
Noncommunicable diseases such as cardiovascular diseases, cancer, and diabetes are the leading cause of morbidity and mortality around the world.1,2 Lack of physical activity is recognized as a major modifiable risk factor of these diseases.3,4 While considering the global burden of noncommunicable diseases, India contributes a major share.1 The state of Kerala has one of the highest prevalence of noncommunicable diseases in the country.5,6
Reprints and permissions: sagepub.com/journalsPermissions.nav Corresponding Author: P. Mayamol, Department of Community Medicine, Academy of Medical Sciences, Kannur 670503, Kerala, India. [email protected]. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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Lifestyle changes such as the adoption of unhealthy diet and physical inactivity are the major factors attributed to the rise in the noncommunicable diseases burden in the state.7 Over the past 2 decades, several studies had reported that the physical activity level among Indians was very low.8–11 The physical activity level in the state of Kerala was assessed using the Global Physical Activity Questionnaire as a part of the nationwide Noncommunicable Disease (NCD) Risk Factor Survey (STEPS—stepwise approach to surveillance) by the World Health Organization (WHO) and the Indian Council for Medical Research (ICMR) in 2003–2004 and 2007–2008. The 2 surveys showed marked difference in level of physical inactivity (5.9% in 2003–2004 and 74.5% in 2007–2008).12,13 Further research is needed to know whether this rise in level of physical inactivity is consistent over time.14 Hence, this study was undertaken to assess the prevalence of low physical activity level among adults aged 15 to 65 years in a village in northern Kerala.
Author Manuscript
Methodology A cross-sectional survey was carried out to assess the level of physical activity among residents of Kulappuram village, which comes under Cheruthazham panchayat in Kannur district, Kerala. The survey was carried out as a part of a health promotion initiative called Model Health Village project of the Community Medicine department Of our institute and Kulappuram Vayanashala, a local nongovernmental organization. The village had a total of 520 houses with 2206 residents in year 2012. The number of residents engaging in agriculture-related activity was less than 100. For the project, the village was divided into 20 clusters based on geography, and each cluster had 25 to 30 houses.
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For the study, a sample size of 240 was estimated after taking into account moderate to highlevel physical activity prevalence of 44% among South Indians as shown in the ICMR INDIAB study, relative precision of 20%, intended power of 80%, and design effect of 1.5.8 Out of the 20 clusters, 4 clusters were randomly selected by the lottery method and 60 individuals within each cluster were included in the study. Residents aged between 15 and 65 years were assessed for physical activity level. Those who were suffering from debilitating diseases or were physical challenged were excluded from the study. All the eligible members of a household in the selected clusters were assessed, and consecutive households were included in study till the required sample size was achieved.
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The study was approved by Institute Ethical Committee of Academy of Medical Sciences, Pariyaram, Kannur, Kerala. The participants were interviewed after obtaining informed consent. The demographic and socioeconomic details of the participants were recorded using a questionnaire. The physical activity level was assessed using Global Physical Activity Questionnaire (GPAQ), which has been validated for Indian settings.15,16 The questionnaire in the local language has been used for the WHO-ICMR NCD risk factor survey (STEPS surveys) in the state.13 The GPAQ assesses self-reported duration and frequency of moderate to vigorous intensity physical activity during work, travel, and in recreation. It also assesses the time spent in sedentary activity.
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The data were entered in Microsoft excel and analyzed using EpiInfo7. As per the guidelines for interpreting GPAQ Version 2.0, individuals were classified as having low, moderate, or high level of physical activity. For this, the total time spent on physical activity during a typical week, the number of days in a week, as well as the intensity of physical activity were taken into account.16 The results were described in proportion, and χ2 test was used to test the significance of association between physical activity and sociodemographic variables. Binary logistic regression analyses (with all independent variables entered simultaneously) were subsequently undertaken to explore associations of the sociodemographic variables with physical activity level (high or moderate physical activity vs low physical activity). The mean duration per day of moderate to vigorous intensity physical activity (MVPA) in different domains as well as that of sedentary activity was estimated, and the differences across sociodemographic variables were tested by ANOVA (with post hoc analysis using Tukey test). Multiple linear regression was executed to identify significance of association of sociodemographic variables with the dependent variables: overall MVPA, work MVPA, recreation MVPA, transport MVPA, and sedentary activity. Sociodemographic variables considered were age (continuous), gender, occupation (3 categories), education (2 categories), marital status (2 categories), type of family (2 categories), income (2 categories), religion (2 categories), and chronic illness (2 categories). Statistical significance was set at . 05.
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Among the 240 study participants, 128 (53.3%) were females and 112 (46.7%) were males. The participants in the younger age groups (15–25 years) constituted 25.4% of the total, and the older age group (56–65 years) constituted 18.3%. About half of the participants (45%) were educated at the high school level or more. Majority (70.8%) of the study participants were Hindus. Only 29.6% of the participants belonged to the below the poverty line group as per the ration card details Table 1).
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In the study, it was found that 65.8% of the participants had low level of physical activity. High level of physical activity was found among 17.9% of the participants, and moderate level of physical activity was seen among 16.3% of the participants. In the logistic regression analysis, it was seen that the level of physical activity was more among those engaged in unskilled work (adjusted odds ratio [OR] = 4.32; confidence interval [CI] = 1.38–13.51) when compared with unemployed/retired persons. Also, higher physical activity level was seen among unmarried persons (adjusted OR = 3.65; CI = 1.25–10.65) when compared with ever married. No statistically significant association of physical activity level was seen with different age group, education, religion, family type, presence of chronic diseases, and economic categories. Overall, the mean time spent in MVPA was found to be 63.4 (standard error [SE] = 7.8) minutes/day (Table 2). The average time of MVPA during work, travel, and recreation was 40.5 (SE 7.8), 10.1 (SE 1.9), and 12.7 (SE 1.9) minutes/day, respectively. The mean duration per day of MVPA across different sociodemographic variables is given in Table 2. Multiple linear regression analysis shows that there is significant association of overall MVPA with occupation (B −44.6, P value .001), marital status (B −81.1, P value .002), and religion (B
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24.9, P value.03) (constant 284.2). Work-related MVPA was significantly associated with occupation (B −41.3, P value.001) and marital status (B −55.1, P value.013) (constant 196.3). Significant association was also found in recreational MVPA with gender (B −8.6, P value .02) and marital status (B −16, P value .01) (constant 19.8). The mean duration of sedentary activity among the study participants was 284.3 minutes per day. The duration of sedentary activity was similar across different age groups, gender, and other sociodemographic variables. The study shows that 75.6% of the study participants had no work-related MVI physical activity. The absence of recreational MVPA was seen in 86.2% of the study participants, and it was more common in females (92.2%) when compared with males (71.4%; P .004).
Discussion Author Manuscript Author Manuscript
The study shows that the majority (65.3%) of the study population had low level of physical activity. Over the past 2 decades, studies assessing the level of physical activity using the GPAQ in different parts of India had shown varied results. The STEPS survey conducted in 2003–2005 showed that physical inactivity was prevalent in 5.9% of the population in rural Kerala.12 However, the STEPS survey in 2007–2008 showed that low level of physical activity was seen in 74.5% of the rural population in Kerala, which was similar to the present study.12 In the STEPS survey 2007–2008, Kerala reported a higher level of physical inactivity when compared to the rural population in neighboring states of Tamil Nadu (61.6%) and Andhra Pradesh (63.8%). The ICMR-INDIAB study showed that low level of physical activity was seen in 55.4% of the rural population in Tamil Nadu.8 In a multisite cross-sectional study done in 2005, the prevalence of physical inactivity in rural India was 53%.9 The level of physical inactivity in the present study was far higher than the global estimate (31.1%) and that for the Southeast Asian region (17%).17 The high level of physical inactivity in the state may be the result of higher education status of its population as a result of which more and more people are preferring non-agriculture or less labor intense jobs.18
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When different domains of physical activity was compared in the study, duration of workrelated physical activity was more when compared with that of recreational- or travel-related physical activity. The average minutes spent per day in MVPA during work was very low in the present study (40.5 minutes/day) when compared with the results the STEPS survey 2007–2008 for rural Kerala (161 minutes/day). This difference may be explained by the fact that only 14% of the study sample was involved in unskilled occupation, which requires intense physical activity, while in the STEP survey, 20% of the sample were involved in such work. In the study, three fourths of the population had no work-related MVPA despite this being a rural population. Decrease in work-related physical activity needed to be compensated by increase recreational physical activity to meet the WHO guidelines of 150 minutes of moderate to vigorous physical activity per week. But the present study shows that the average recreational MVPA was only 10 minutes/day, lower than the STEPS survey for rural Kerala (15 minutes/day). Recreation MVPA was absent in 86.7% of the study participants in the present study. This was similar to the results from the INDIAB study, which reported lack of recreational MVPA among more than 90% of the rural population in India. The present study reported a low level of recreational MVPA among females when
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compared with males. Several studies conducted in India reported similar finding and this can be due to cultural factors in the country, which restrict the participation of women in outdoor sports.8,13,19 Several studies show that age group, gender, urban living, religion, education, and occupation can be associated with physical activity level.8,20 In the present study, only occupation category (unskilled job vs unemployed/retired) and marital status (unmarried over ever married) were the factors that were significantly associated with physical activity level.
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There are some limitations for this study. Since the study was using the GPAQ as an assessment tool, problems with self-reporting like overreporting or underreporting of physical activity cannot be ruled out. Also, many activities described in the GPAQ may not be culturally specific or relevant. Since the GPAQ counts only those activities done for a minimum duration of 10 minutes, many activities such as household work of housewifes may not be taken into account. Another limitation was that the sample size calculation was powered to detect the prevalence of moderate to high physical activity level and not for establishing association with any variable. Hence, the study was not able identify significant factors associated with physical inactivity.
Conclusion
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The study shows that level of physical activity among the rural population of Kerala was alarmingly low. To reduce the burden of noncommunicable disease in the state, there is an urgent need to improve the overall physical activity level. As more sections of the rural population are getting employed in sedentary occupation categories, there is a need to promote recreational physical activities. This should begin early in life, at the school level, so that such activities become part of their lifestyle.
Acknowledgments Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: PM is supported by the ASCEND program which is funded by the Fogarty International Center at the United States’ National Institutes of Health (NIH), under Award Number D43TW008332 (ASCEND Research Network). The contents of this report are solely the responsibility of the authors, and do not necessarily represent the official views of the National Institutes of Health.
References Author Manuscript
1. World Health Organization. Global Status Report on Noncommunicable Diseases 2014. Geneva, Switzerland: World Health Organization; 2014. 2. Ramahi TM. Cardiovascular disease in the Asia Middle East region: global trends and local implications. Asia Pac J Public Health. 2010; 22(3 suppl):83S–89S. [PubMed: 20566538] 3. Lee IM, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. 2012; 380:219–229. [PubMed: 22818936] 4. Li Y, Sato Y, Yamaguchi N. Lifestyle factors as predictors of general cardiovascular disease: use for early self-screening. Asia Pac J Public Health. 2014; 26:414–424. [PubMed: 22156564]
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5. Mohan V, Pradeepa R. Epidemiology of diabetes in different regions of India. Health Administrator. 2009; 22(1):1–18. 6. Raman Kutty V, Balakrishnan K, Jayasree A, Thomas J. Prevalence of coronary heart disease in the rural population of Thiruvananthapuram district, Kerala, India. Int J Cardiol. 1993; 39:59–70. [PubMed: 8407009] 7. Sivasankaran S, Thankappan KR. Prevention of non-communicable diseases requires a life course approach: a case study from Kerala. Indian J Med Res. 2013; 137:874–877. [PubMed: 23760370] 8. Anjana RM, Pradeepa R, Das AK, et al. Physical activity and inactivity patterns in India—results from the ICMR-INDIAB study (Phase-1) [ICMR-INDIAB-5]. Int J Behav Nutr Phys Act. 2014; 11:26. [PubMed: 24571915] 9. Ng N, Hakimi M, Van Minh H, et al. Prevalence of physical inactivity in nine rural INDEPTH Health and Demographic Surveillance Systems in five Asian countries. Glob Health Action. 2009; 2 10. Krishnan A, Shah B, Lal V, Shukla DK, Paul E, Kapoor SK. Prevalence of risk factors for noncommunicable disease in a rural area of Faridabad district of Haryana. Indian J Public Health. 2008; 52:117–124. [PubMed: 19189832] 11. Sugathan TN, Soman CR, Sankaranarayanan K. Behavioural risk factors for non-communicable diseases among adults in Kerala, India. Indian J Med Res. 2008; 127:555–563. [PubMed: 18765874] 12. Division of Non-communicable Diseases, Indian Council of Medical Research. Development of Sentinel Health Monitoring Centers for Surveillance of Risk Factors of Noncommunicable Diseases in India (April 2003 to March 2005): Collated Results of 6 Centers. New Delhi, India: Indian Council of Medical Research; 2005. 13. National Institute of Medical Statistics, Indian Council of Medical Research. IDSP NonCommunicable Disease Risk Factors Survey, Phase-I States of India, 2007-08. New Delhi, India: National Institute of Medical Statistics and Division of Non-Communicable Diseases, Indian Council of Medical Research; http://www.icmr.nic.in/final/IDSP-NCDReports/ Phase-1StatesofIndia.pdf. Published 2009 [Accessed February 17, 2015] 14. Ranasinghe CD, Ranasinghe P, Jayawardena R, Misra A. Physical activity patterns among SouthAsian adults: a systematic review. Int J Behav Nutr Phys Act. 2013; 10:116. [PubMed: 24119682] 15. Bull FC, Maslin TS, Armstrong T. Global physical activity questionnaire (GPAQ): nine country reliability and validity study. J Phys Act Health. 2009; 6:790–804. [PubMed: 20101923] 16. World Health Organization. Global Physical Activity Questionnaire—Analysis guide. http:// www.who.int/chp/steps/resources/GPAQ_Analysis_Guide.pdf. 17. Hallal PC, Andersen LB, Bull FC, et al. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet. 2012; 380:247–257. [PubMed: 22818937] 18. Office of Registrar General. [Accessed June 29, 2015] Executive Summary: Kerala Census. http:// www.censusindia.gov.in/2011census/PCA/PCA_Highlights/pca_highlights_file/kerala/ Exeutive_Summary.pdf 19. Kinra S, Bowen LJ, Lyngdoh T, et al. Sociodemographic patterning of non-communicable disease risk factors in rural India: a cross sectional study. BMJ. 2010; 341:c4974. [PubMed: 20876148] 20. Katulanda P, Jayawardena R, Ranasinghe P, Rezvi Sheriff MH, Matthews DR. Physical activity patterns and correlates among adults from a developing country: the Sri Lanka Diabetes and Cardiovascular Study. Public Health Nutr. 2013; 16:1684–1692. [PubMed: 22995708]
Author Manuscript Asia Pac J Public Health. Author manuscript; available in PMC 2016 April 21.
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Asia Pac J Public Health. Author manuscript; available in PMC 2016 April 21. 10 72
No illness
60
Chronic illness
22
Below poverty line
64
Above poverty line
18
Joint
11
Nuclear
40.0
16
Muslim Christian
36.0
25.0
35.5
31.0
33.3
37.5
36.7
32.4
42.6
31.3
42.0
27.3
35.4
32.7
48.6
32.1
31
38.6
34.7
29.5
33.3
34.4
%
55
26
Unmarried Hindu
56
47
Male Ever married
35
46
High school Female
36
17
Unskilled jobs Higher secondary or above
43
17
56–65 22
17
46–55
Unemployed, retired
13
Skilled: clerical, business, professionals, housewife, semiprofessionals
14
36–45
21
n
26–35
15–25
Abbreviations: OR, odds ratio; CI, confidence interval.
Chronic illness
Economic class
Type of family
Religion
Marital status
Gender
Education
Occupation
Age group
Categories
Moderate or High Physical Activity
128
30
109
49
128
30
19
24
115
35
123
65
93
84
74
18
91
49
27
32
31
28
40
n
64.0
75.0
64.5
69.0
66.7
62.5
63.3
60.0
67.6
57.4
68.7
58.0
72.7
64.6
67.3
51.4
67.9
69
61.4
65.3
70.5
66.7
65.6
%
Low Physical Activity
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Level of Physical Activity Across Different Subgroups of the Study Sample.
.2
.5
.6
.6
.1
.02
.6
.15
.9
P Value
2.35
1.35
0.79
1.43
1.55
3.65
1.57
1.18
2.47
4.32
2.90
1.42
1.10
1.00
Adjusted OR
0.94–5.86
0.67–2.70
0.38–1.65
0.6–3.37
0.69–3.48
1.25–10.65
0.87–2.83
0.59–2.39
0.94–6.48
1.38–13.51
0.79–10.68
0.36–5.64
0.30–4.02
0.31–3.21
95% CI
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Table 1 Aslesh et al. Page 7
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Author Manuscript 27.2 34.4 66.9 54.4
26–35
36–45
46–55
56–65
30.5
Female
38.3 15.0
Skilled: clerical, business, professionals, housewife, semiprofessionals
Unemployed, retired
22.2
Higher secondary or above
Asia Pac J Public Health. Author manuscript; available in PMC 2016 April 21. 41.9
Ever married
70.9
Christian
Nuclear
40.8
16.7
Muslim
Type of family
40.7
Hindu
Religion
36.3
Unmarried
Marital status
55.9
High school
Education
100.4
Unskilled
Occupation
51.8
Male
Gender
22.6
15–25
Age group
Mean
7.4
28.5
9.0
7.6
8.2
10.7
6.4
10.9
5.9
8.4
28.7
8.7
10.3
17.7
20.1
15.3
11.5
8.9
SE
.9
.1
.7
.01
.001b
.1
.4
Work-Related MVPA Duration
9.2
8.2
24
7.0
5.1
24.4
15.1
5.7
17.0
7.7
4.4
5.0
15.9
7.2
1.1
8.4
11.2
19.6
Mean
2.1
4.1
7.3
1.9
1.4
5.9
3.4
2.0
4.8
2.0
3.7
1.7
3.5
3.5
0.7
3.7
4.2
5.7
SE
.4
.004d
.001
.02
.05
.004
.02a
Recreation-Related MVPA Duration
13.9
24.3
13.4
10.5
11.2
17.0
12.4
12.9
13.1
10.4
20.7
10.1
15.7
10.4
16.8
9.1
8.2
16.7
Mean
2.2
8.1
4.6
1.9
2.0
4.3
2.4
2.5
3.6
2.2
5.8
2.2
3.1
3.9
4.6
3.9
3.3
4.3
SE
.2
.05
.2
.9
.2
.1
0.4
Travel-Related MVPA Duration
63.9
103.5
54.1
58.2
58.2
77.8
49.7
74.5
45.1
56.4
125.6
45.5
83.3
72.5
84.8
51.9
46.6
58.9
Mean
8.8
30.1
13.8
9.1
8.9
16.3
9.5
11.8
10.6
9.4
31.7
9.4
12.6
18.5
21.7
16.8
14.7
14.9
SE
.8
.1e
.3
.1
.003c
.01
.5
Overall MVPA Duration
Mean Duration (in Minutes per Day) of Moderate to Vigorous Intensity Physical Activity (MVPA) at Work, Recreation, and Travel Among the Study Participants Across Different Sociodemographic Variables.
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Table 2 Aslesh et al. Page 8
Author Manuscript 40.5
All
6.8
6.7
21.8
.2
10.1
2.1
11.6
11.5
9.3
1.9
1.6
2.2
4.0
2.1
4.3
SE
.07
.6
12.7
8.2
13.6
10.7
13.6
8.0
Mean
1.9
3.0
2.1
3.5
2.2
3.4
SE
.2
.5
63.2
66.8
62.4
73.5
58.8
60.3
Significant difference in transport-related physical activity duration (P < .05) between Hindus and Christians.
Significant difference in recreational physical activity duration (P < .05) between Hindus and Muslims.
7.8
22.6
8.3
17.4
8.4
17.0
SE
.8
.4
Overall MVPA Duration Mean
Significant difference in total physical activity duration between unskilled and skilled/business/clerical group as well as between unskilled and unemployed/retired.
d
e
56.4
Chronic illness
.3
13.0
Mean
Travel-Related MVPA Duration
Significant difference in work-related physical activity duration between unskilled and skilled/business/clerical group as well as between unskilled and unemployed/retired.
b
c
37.3
No illness
14.9
7.2
15.2
SE
Significant difference in recreational physical activity duration (P < .05) between age group 15–25 years and 46–55 years.
a
51.4
Below poverty line
Chronic illness
35.9
39.2
Mean
Above poverty line
Economic class
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Author Manuscript Recreation-Related MVPA Duration
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Work-Related MVPA Duration
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