CAJGH_Template New articles in this journal are licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by theUniversity Library System of the University of Pittsburgh as part of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. Patterns of Physical Activity and Self-rated Health Among Adult Populations in South Asia Sanni Yaya1*, Ghose Bishwajit1,2* 1Faculty of Social Sciences, School of International Development and Global Studies, University of Ottawa, Canada; 2Institute of Nutrition and Food science, University of Dhaka, Bangladesh *Equal contributors Vol. 9, No. 1 (2020) | ISSN 2166-7403 (online) DOI 10.5195/cajgh.2020.347 | http://cajgh.pitt.edu http://www.library.pitt.edu/ http://www.pitt.edu/ http://www.library.pitt.edu/articles/digpubtype/index.html http://www.upress.pitt.edu/upressIndex.aspx http://creativecommons.org/licenses/by/3.0/us/ YAYA This work is licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by theUniversity Library System of the University of Pittsburgh as part of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. Central Asian Journal of Global Health Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.347|http://cajgh.pitt.edu Abstract Introduction: Although South Asians are considered to be at high risk for cardiovascular diseases, research evidence on the health impacts of physical activity (PA) remains very limited. In this study we aimed to explore the patterns of PA and to investigate whether engaging in regular PA is associated with better Self-Rated Health (SRH) among South Asians. Methods: Cross-sectional data on population health were drawn from the World Health Survey of WHO. Subjects were 28,020 male and female South Asians (from Bangladesh, India, Nepal, and Sri Lanka) aged 18 years and above. Data were analysed using descriptive and multivariable logistic regression analyses. Results: The proportion of the sample population reported good SRH was 44.3%, 58.7%, 37.7%, and 73.7% in Bangladeshis, Indians, Nepalese, and Sri Lankans, respectively. Regular engagement in moderate PA was highest in Nepal (69.7%) and lowest in Bangladesh (37.4%). Vigorous PA was highest in India (29.9%) and lowest in Bangladesh (17.9%). In Bangladesh, compared to those never engaged in MPA, those who engaged for 1-2, 3-4, 5-6, or 7 days a week were 30% [AOR=1.306; 95%CI 1.085- 1.572], 33% [AOR=1.326; 95%CI 1.093-1.609], 39% [AOR=1.389; 95%CI 1.125-1.716], and 46% [AOR=1.459; 95%CI 1.249- 1.705] more likely to report being in good health, respectively. Conclusions: We found that self-reported engagement in physical activities varies in South Asian countries. Since engaging in PA may help improve subjective and objective health status, health policy makers need to focus on designing exercise-friendly neighbourhoods in an attempt to promote population health. Keywords: Moderate Physical Activity; Vigorous Physical Activity; Self-Rated Health; South Asia; World Health Survey Patterns of Physical Activity and Self- rated Health Among Adult Populations in South Asia Sanni Yaya1*, Ghose Bishwajit1,2* 1Faculty of Social Sciences, School of International Development and Global Studies, University of Ottawa, Canada; 2Institute of Nutrition and Food science, University of Dhaka, Bangladesh Research Introduction The construct of self-rated health (SRH) is an inclusive measure of public health, and it is used as a reliable predictor of quality of life, subjective well-being, disability, morbidity, and mortality1,2. SRH is one of the most widely used predictors of health risk and prognosis compared with/to other objective measures3. Possible explanations for the efficacy of self-assessments of health include its multifaceted representation of an individual’s general perception of health, including biological, psychosocial, and cultural dimensions of health and expressiveness4. SRH has also been found to be related to clinical measures of health3, and it was proposed that general practitioners can utilize SRH measures in clinical encounters5. Moreover, SRH can be regarded as a more inclusive measure of health status than clinical diagnosis, as it tends to be sensitive to social determinants of health such as education, socioeconomic status, and living conditions, which have direct influences on health and well-being and on shaping individuals perception of health and illness4,5. SRH is therefore able to provide information above and beyond typical clinical evaluation and thus offers a http://www.library.pitt.edu/ http://www.pitt.edu/ http://www.library.pitt.edu/articles/digpubtype/index.html http://www.upress.pitt.edu/upressIndex.aspx http://www.upress.pitt.edu/upressIndex.aspx CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH This work is licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by theUniversity Library System of the University of Pittsburgh as part of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. Central Asian Journal of Global Health Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.347|http://cajgh.pitt.edu comprehensive way of assessing a patients’ overall health status4,6. In recent years, there has been an increasing research interest on the impact of various lifestyle factors and health related behaviours on SRH7,8. Behavioural aspects, such as tobacco smoking, alcohol drinking, dietary habits, and engaging in physical activity (PA) are explored in relation to how they correlate with SRH among people of different age groups and socioeconomic backgrounds. Physical inactivity is regarded as a growing public health issue both in developed and developing countries. In Europe and other industrialised societies, increasing sedentary lifestyle has been shown to be associated with worse health and all-cause mortality, independent of level of PA9-11. According to WHO, public health burden of physical inactivity is high and causes an estimated 600,000 deaths per year in Europe alone11. Worldwide, physical inactivity is responsible for 6% of the burden of coronary heart disease, 7% of type 2 diabetes, and 10% of breast and colon cancer12. It has also been identified as the fourth leading risk factor for global mortality in 2010, accounting for roughly 13.4 million disability adjusted life years (DALYs)15 and 6% of all deaths13. There is a growing consensus that moderate- to vigorous- intensity PA has a key preventive role in non- communicable diseases (NCDs), including obesity, cardiovascular disease, type-2 diabetes, and some cancers9,10. Lack of PA during adolescence was reported to be a significant predictor of abdominal obesity in young adulthood leading to a self-perpetuating vicious circle of obesity and physical inactivity14. In addition to its contribution to increased morbidity and mortality, physical inactivity is also responsible for a substantial economic burden. Epidemiological evidence on the role of PA on SRH is necessary for making informed health policies that can promote PA in the general population. South Asians are people who identify with the cultures of Bangladesh, India, Sri Lanka, and Nepal, and account for about a quarter of the global population with a unique epidemiological and sociodemographic profile. Though South Asians are considered at-risk population for cardiovascular diseases, research evidence on the health impacts of PA in this population remains very limited. Therefore, epidemiological evidence from other regions may not be applicable for the population in this region. This study was carried out to provide insights on the pattern of PA in South Asians, and to investigate the association between frequency of PA and SRH among the adult population. Data used in this study were extracted from the World Health Survey program of WHO conducted during 2002-2004 that included four South Asian countries: Bangladesh, India, Nepal, and Sri Lanka. Methods Data source This study was based on the data extracted from WHO World Health Survey conducted between 2002 and 2004, available from WHO upon request. Objectives of the WHO-funded survey were to provide reliable and nationally comparable data on a wide range of health and socioeconomic indicators to facilitate evidence-based health policy making. These data are utilized by many researchers due to lack of more recent data on health behaviour and self-rated health in South Asian population. The program is operational in 70 countries including four South Asian countries: Bangladesh, India, Nepal, and Sri Lanka. Further details regarding the original survey study are published elsewhere16. Variables of interest Self-rated health status was the outcome variable in this study. Emerging evidence suggests predictability of SRH for both non-clinical and clinical outcomes, and it is being proposed to family physicians as an efficient yet simple way for therapeutic decision making28,29. Respondents were asked to rate their health on a scale from 1 to 5 with the following response http://www.library.pitt.edu/ http://www.pitt.edu/ http://www.library.pitt.edu/articles/digpubtype/index.html http://www.upress.pitt.edu/upressIndex.aspx YAYA This work is licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by theUniversity Library System of the University of Pittsburgh as part of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. Central Asian Journal of Global Health Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.347|http://cajgh.pitt.edu Variables Bangladesh India Nepal Sri Lanka (n=5462) (n=8853) (n=8031) (n=5674) Age, Mean (SD) 38.47 (14.81) 38.69 (15.07) 38.55 (15.33) 40.78 (15.22) 18-29 1688 30.9 2771 31.3 2666 33.2 1515 26.7 30-39 1502 27.5 2275 25.7 2008 25 1367 24.1 40-49 1103 20.2 1611 18.2 1462 18.2 1231 21.7 50-59 574 10.5 1054 11.9 867 10.8 823 14.5 60+ 595 10.9 1151 13 1028 12.8 743 13.1 Sex Female 2917 53.4 4515 51 4602 57.3 2968 52.3 Male 2545 46.6 4338 49 3429 42.7 2706 47.7 Currently married No 1218 22.3 2036 23 1413 17.6 1765 31.1 Yes 4244 77.7 6817 77 6618 82.4 3909 68.9 Educational attainment Nil 2245 41.1 3400 38.4 4819 60 318 5.6 Less than primary school 1000 18.3 832 9.4 883 11 431 7.6 Primary complete 1360 24.9 44 0.5 1108 13.8 1430 25.2 Secondary complete 404 7.4 1567 17.7 819 10.2 2236 39.4 High school/ equivalent complete 218 4 1142 12.9 257 3.2 1123 19.8 Pre-university/ University 235 4.3 894 10.1 137 1.7 136 2.4 Employment status Govt. employee 197 3.6 336 3.8 249 3.1 511 9 Private employee 333 6.1 974 11 169 2.1 647 11.4 Employer 2081 38.1 3621 40.9 5381 67 1923 33.9 Not working for payment 2851 52.2 3940 44.5 2225 27.7 2599 45.8 Smoking habit Daily 2021 37 2780 31.4 3212 40 726 12.8 Yes. not daily 300 5.5 266 3 385 4.8 460 8.1 Non-smoker 3141 57.5 5808 65.6 4433 55.2 4494 79.2 http://www.library.pitt.edu/ http://www.pitt.edu/ http://www.library.pitt.edu/articles/digpubtype/index.html http://www.upress.pitt.edu/upressIndex.aspx http://www.upress.pitt.edu/upressIndex.aspx CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH This work is licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by theUniversity Library System of the University of Pittsburgh as part of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. Central Asian Journal of Global Health Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.347|http://cajgh.pitt.edu Table 1. Sample characteristics. options: 1. Very good; 2. Good; 3. Moderate; 4. Bad; and 5. Very Bad. SRH was analysed dichotomously as: 1) Good SRH (Very good and Good), and 2) Poor SRH (Moderate, Bad and Very Bad)30. The validity of the single-item tool to measure subjective health was mentioned in previous studies31,32. The predictor variable of primary interest was PA. The two types of PA used in this study were moderate PA (MPA) and vigorous PA (VPA). VPA was measured by the following question: “Vigorous activities make you breathe much harder than normal and may include heavy lifting, digging, aerobics, or fast bicycling. Think only about those physical activities that you performed for at least 10 minutes at a time. During the last 7 days, on how many days did you do vigorous physical activities?” MPA was measured by the following question: “Moderate physical activities make you breathe somewhat harder than normal and may include carrying light loads, bicycling at a regular pace, or doubles tennis. Do not include walking. Again, think about only those physical activities that you performed for at least 10 minutes at a time. During the last 7 days, on how many days did you do moderate physical activities?” Answers ranged from 0 to 7 days and were categorised as follows: 0 days (never), 1-2 days, 3-4 days, 5-6 days, and every day. The other potential predictor variables included in the study were: Age (18-29/30-39/40-49/50-59/60+ years); Sex (Female/Male); Currently married (No/Yes); Educational attainment (Nil/ Less than primary school/ Primary complete/ Secondary complete/ High school/equivalent complete/ Pre-university/ University); Employment status (Government employee/ Private employee/ Employer/ Unemployed); Smoking habit (Daily/Yes, but not daily/Non-smoker); Ever drank alcohol (Yes/No). Ethical considerations Informed Consent was obtained from the recruited participants before their participation in the survey. Participation was completely voluntary, and the respondent had the choice to refuse to take part in the interview. The data used in this study were secondary, Ever drank alcohol Yes 360 6.6 965 10.9 2883 35.9 965 17 No 5102 93.4 7888 89.1 5148 64.1 4709 83 Days of MPA 0 1262 23.1 1505 17 1108 13.8 1010 17.8 1-2 852 15.6 558 6.3 369 4.6 460 8.1 3-4 748 13.7 629 7.1 498 6.2 630 11.1 5-6 557 10.2 1062 12 450 5.6 755 13.3 7 2043 37.4 5099 57.6 5598 69.7 2820 49.7 Days of VPA 0 2709 49.6 3824 43.2 3975 49.5 2582 45.5 1-2 754 13.8 735 8.3 771 9.6 545 9.6 3-4 606 11.1 646 7.3 899 11.2 499 8.8 5-6 410 7.5 1000 11.3 426 5.3 681 12 7 978 17.9 2647 29.9 1960 24.4 1367 24.1 http://www.library.pitt.edu/ http://www.pitt.edu/ http://www.library.pitt.edu/articles/digpubtype/index.html http://www.upress.pitt.edu/upressIndex.aspx YAYA This work is licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by theUniversity Library System of the University of Pittsburgh as part of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. Central Asian Journal of Global Health Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.347|http://cajgh.pitt.edu Bangladesh India Nepal Sri Lanka Good SRH (44.3) Poor SRH (55.7) Good SRH (58.7) Poor SRH (41.3) Good SRH (37.7) Poor SRH (62.3) Good SRH (73.7) Poor SRH (26.3) n % n % n % n % n % n % n % n % Age 18-29 2092 38.3 1371 25.1 3444 38.9 1815 20.5 3100 38.6 1952 24.3 1838 32.4 607 10.7 30-39 1639 30 1393 25.5 2461 27.8 2010 22.7 2120 26.4 1831 22.8 1515 26.7 942 16.6 40-49 1005 18.4 1180 21.6 1478 16.7 1788 20.2 1446 18 1486 18.5 1265 22.3 1135 20 50-59 404 7.4 705 12.9 859 9.7 1328 15 747 9.3 1068 13.3 664 11.7 1265 22.3 60+ 322 5.9 814 14.9 611 6.9 1921 21.7 626 7.8 1687 21 392 6.9 1725 30.4 P <0.0001 <0.0001 <0.0001 <0.0001 Sex Female 2797 51.2 3015 55.2 4241 47.9 4905 55.4 4578 57 4642 57.8 2865 50.5 3257 57.4 Male 2665 48.8 2447 44.8 4612 52.1 3948 44.6 3453 43 3389 42.2 2809 49.5 2417 42.6 P 0.002 <0.0001 0.175 <0.0001 Currently married No 1191 21.8 1240 22.7 2125 24 1903 21.5 1333 16.6 1542 19.2 1765 31.1 1770 31.2 Yes 4271 78.2 4222 77.3 6728 76 6950 78.5 6698 83.4 6489 80.8 3909 68.9 3904 68.8 P <0.0001 <0.0001 <0.0001 <0.0001 Educational attainment Nil 2103 38.5 2354 43.1 2939 33.2 4046 45.7 4634 57.7 5116 63.7 227 4 579 10.2 Less than primary school 945 17.3 1043 19.1 691 7.8 1036 11.7 916 11.4 835 10.4 340 6 692 12.2 Primary complete 1431 26.2 1305 23.9 35 0.4 44 0.5 1205 15 956 11.9 1316 23.2 1748 30.8 Secondary complete 415 7.6 393 7.2 1470 16.6 1709 19.3 851 10.6 771 9.6 2326 41 1963 34.6 High school/ equivalent 262 4.8 186 3.4 1328 15 876 9.9 297 3.7 201 2.5 1305 23 613 10.8 Pre- university/ University 306 5.6 180 3.3 1142 12.9 531 6 137 1.7 145 1.8 159 2.8 74 1.3 P <0.0001 <0.0001 <0.0001 <0.0001 http://www.library.pitt.edu/ http://www.pitt.edu/ http://www.library.pitt.edu/articles/digpubtype/index.html http://www.upress.pitt.edu/upressIndex.aspx http://www.upress.pitt.edu/upressIndex.aspx CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH This work is licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by theUniversity Library System of the University of Pittsburgh as part of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. Central Asian Journal of Global Health Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.347|http://cajgh.pitt.edu Employment status Govt. employee 235 4.3 169 3.1 425 4.8 204 2.3 257 3.2 233 2.9 550 9.7 397 7 Private employee 388 7.1 289 5.3 1107 12.5 779 8.8 177 2.2 161 2 721 12.7 437 7.7 Employer 2687 49.2 2021 37 4621 52.2 3444 38.9 5590 69.6 5051 62.9 2480 43.7 1923 33.9 Not working for payment 2157 39.5 2683 54. 6 3594 40.6 4427 50 2008 25 2586 32.2 1918 33.8 2916 51.4 P <0.0001 <0.0001 <0.0001 <0.0001 Smoking habit Daily 2092 38.3 2261 41.4 2470 27.9 3222 36.4 2883 35.9 3116 38.8 704 12.4 783 13.8 Yes. not daily 262 4.8 257 4.7 257 2.9 274 3.1 418 5.2 482 6 443 7.8 494 8.7 Non-smoker 3108 56.9 2944 53.9 6126 69.2 5356 60.5 4730 58.9 4433 55.2 4528 79.8 4397 77.5 P <0.0001 <0.0001 <0.0001 <0.0001 Ever drank alcohol Yes 328 6 388 7.1 983 11.1 956 10.8 2819 35.1 2980 37.1 993 17.5 891 15.7 No 5134 94 5074 92.9 7870 88.9 7897 89.2 5212 64.9 5051 62.9 4681 82.5 4783 84.3 P <0.0001 <0.0001 <0.0001 <0.0001 Days of MPA 0 863 15.8 2807 51.4 505 5.7 1726 19.5 353 4.4 4538 56.5 448 7.9 1566 27.6 1-2 1010 18.5 787 14.4 1346 15.2 637 7.2 883 11 715 8.9 811 14.3 488 8.6 3-4 770 14.1 590 10.8 593 6.7 673 7.6 498 6.2 795 9.9 635 11.2 596 10.5 5-6 590 10.8 410 7.5 992 11.2 1151 13 385 4.8 450 5.6 817 14.4 596 10.5 7 2228 40.8 874 16 5409 61.1 4666 52.7 5903 73.5 1534 19.1 2956 52.1 2428 42.8 P <0.0001 <0.0001 <0.0001 <0.0001 Days of VPA 0 716 13.1 1469 26.9 735 8.3 4241 47.9 811 10.1 1478 18.4 601 10.6 3387 59.7 1-2 2584 47.3 847 15.5 3523 39.8 744 8.4 3638 45.3 402 5 2292 40.4 386 6.8 3-4 634 11.6 726 13.3 664 7.5 629 7.1 956 11.9 498 6.2 499 8.8 511 9 5-6 415 7.6 530 9.7 930 10.5 1098 12.4 418 5.2 562 7 755 13.3 482 8.5 7 1114 20.4 1890 34.6 3001 33.9 2142 24.2 2217 27.6 5084 63.3 1532 27 908 16 P <0.0001 <0.0001 <0.0001 <0.0001 Table 2. Self-rated Health (SRH) results breakdown in Bangladesh, India, Nepal and Sri Lanka, WHS 2002-03 http://www.library.pitt.edu/ http://www.pitt.edu/ http://www.library.pitt.edu/articles/digpubtype/index.html http://www.upress.pitt.edu/upressIndex.aspx YAYA This work is licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by theUniversity Library System of the University of Pittsburgh as part of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. Central Asian Journal of Global Health Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.347|http://cajgh.pitt.edu which are available in the public domain in anonymised form. Additional approval was therefore was not necessary according to WHO regulations (https://www.who.int/healthinfo/survey/en/). Statistical analysis Datasets were checked for missing values and outliers. Data were cleaned to retain the maximum number of observations. Sample characteristics were analysed through univariate analysis. Cross tabulation was used to measure the distribution of the sociodemographic variables across the outcome SRH variable. Chi-square tests were conducted to assess the group differences for Good vs. Poor self-rated health. Variables that had a p-value below 0.25 were entered into the final regression analysis17. Four separate regression models were run for each country. The outcomes of the regression (binary logistic) analyses were reported in terms of adjusted odds ratios (AOR) and corresponding 95% confidence intervals. All analyses were performed with SPSS version 22. Results Descriptive sample characteristics were provided in Table 1. In short, the mean age was highest in Sri Lankans (40.78, SD 15.22) and lowest in Bangladeshis (38.47, SD 14.81). The majority of the participants were between 18 and 29 years of age, female, and currently married. Rate of literacy was highest for Sri Lanka (94.4%) and lowest in Nepal (40%). However, the rate of pre-university/university level education was highest in India (10.1%), followed by Bangladesh (4.3%) and Sri Lanka (2.4%). Regular engagement in MPA was highest for Nepal (69.7%), followed by India (57.6%), Sri Lanka (49.7%), and Bangladesh (37.4%), and that for VPA was highest in India (29.9%) followed by Nepal (24.4%), Sri Lanka (24.1%), and Bangladesh (17.9%). Table 2 shows that the prevalence of good SRH was highest in Sri Lanka (73.7%) and lowest in Nepal (37.7%), while in Bangladesh over two-fifth (44.3%) and in India (58.7%) a little less than three-fifth of the population reported being in good health. Results of cross-tabulation also showed that people who reported good SRH were more likely to be in the younger age groups, female, currently married, having no formal education (except for Sri Lanka), self-employed, non- smoker, and never drinking alcohol. Those who reported engaging in any type of physical activities were also more likely to report being in good health. Results of multivariable regression are shown in Table 3. Results indicate that Bangladeshis who engaged in 1-2, 3-4, 5-6, and 7 days a week were respectively 31% [AOR=1.306; 95%CI 1.085-1.572], 33% [AOR=1.326; 95%CI 1.093-1.609], 39% [AOR=1.389; 95%CI 1.125- 1.716], and 46% [AOR=1.459; 95%CI 1.249-1.705] more likely to report being in good health compared to those who never engaged in MPA. In Sri Lanka, the odds of being in good health were respectively 49% [AOR=1.490; 95%CI 1.164-1.908], 80% [AOR=1.802; 95%CI=1.433-2.266], 2.3 times [AOR=2.255; 95%CI=1.805-2.817], and 86% [AOR=1.854; 95%CI=1.579-2.177] higher among those who those who engaged in MPA for 1-2, 3-4, 5-6 and 7 days a week. In Bangladesh, India, and Nepal, those who engaged in VPA on daily basis were respectively 21% [AOR=1.212; 95%CI 1.033-1.421], 34% [AOR=1.340; 95%CI 1.186-1.512], 36% [AOR=1.363; 95%CI 1.201- 1.547], 22% [AOR=2.224; 95%CI 1.879-2.633] more likely to report being in good SRH compared to those who never engaged in VPA. Among Sri Lankans, the odds of being in good SRH were respectively 2 times [AOR=1.995; 95%CI 1.575-2.527], 25% [AOR=1.255; 95%CI 1.007-1.564], 2.04 times [AOR=2.036; 95%CI=1.644-2.521], and 2.22 times [AOR=2.224; http://www.library.pitt.edu/ http://www.pitt.edu/ http://www.library.pitt.edu/articles/digpubtype/index.html http://www.upress.pitt.edu/upressIndex.aspx http://www.upress.pitt.edu/upressIndex.aspx https://www.who.int/healthinfo/survey/en/ CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH This work is licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by theUniversity Library System of the University of Pittsburgh as part of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. Central Asian Journal of Global Health Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.347|http://cajgh.pitt.edu 95%CI 1.879-2.633] higher among those who engaged in VPA for 1-2, 3-4, 5-6, and 7 days a week. Discussion This is one of the first studies that reports on the association between PA and SRH in a South Asian sample population. Findings of this study indicate a suboptimal level of PA among the adult population in Variables Bangladesh India Nepal Sri Lanka Odds ratio (95%CI) Odds ratio (95%CI) Odds ratio (95%CI) Odds ratio (95%CI) Days of MPA 0 - - - - 1-2 1.306 0.913 1.186 1.490 (1.085-1.572) (0.654-1.010) (0.925-1.519) (1.164-1.908) 3-4 1.326 0.926 1.289 1.802 (1.093-1.609) (0.752-1.142) (1.028-1.615) (1.433-2.266) 5-6 1.389 0.894 0.930 2.255 (1.125-1.716) (0.693-1.004) (0.739-1.169) (1.805-2.817) 7 1.459 1.055 1.478 1.854 (1.249-1.705) (0.919-1.211) (1.283-1.702) (1.579-2.177) Days of VPA 0 - - - - 1-2 0.854 1.024 1.110 1.995 (0.721-1.012) (0.857-1.222) (0.939-1.313) (1.575-2.527) 3-4 1.025 1.103 1.178 1.255 (0.852-1.233) (0.922-1.343) (1.003-1.382) (1.007-1.564) 5-6 0.962 0.959 0.894 2.036 (0.772-1.198) (0.815-1.129) (0.722-1.106) (1.644-2.521) 7 1.212 1.340 1.363 2.224 (1.033-1.421) (1.186-1.512) (1.201-1.547) (1.879-2.633) Table 3. Multivariable analysis on the association between PA and SRH in selected South Asian countries, WHS 2002-03. South Asia. Within subgroups, variations were observed in PA. Findings showed that participants from Bangladesh had the lowest proportion of engaging in any type of PA. Similar results on low prevalence of PA were reported by previous studies from Bangladesh33 and India34. Findings suggest that the percentage of good SRH decreased with age in all countries. Female participants were more likely to report good SRH compared to/with males in all countries except for in India. A noticeable variation was observed in the prevalence of SRH among the four countries. Another important disparity was that having higher frequency of participation in PA did not always relate to higher rate of good SRH. For instance, compared to Sri Lanka, participants from Nepal had lower rates of reporting good SRH despite their higher frequency of involvement in both VPA and MPA. A possible connection might be higher living standards of Sri Lanka compared to the other countries measured in terms of Human Development Index (HDI). The correlation between higher educational status and better health outcomes are well documented across countries18,19. Our results further http://www.library.pitt.edu/ http://www.pitt.edu/ http://www.library.pitt.edu/articles/digpubtype/index.html http://www.upress.pitt.edu/upressIndex.aspx YAYA This work is licensed under a Creative Commons Attribution 4.0 United States License. This journal is published by theUniversity Library System of the University of Pittsburgh as part of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. Central Asian Journal of Global Health Volume 9, No. 1 (2020) | ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2020.347|http://cajgh.pitt.edu indicate that the rate of both moderate and vigorous type physical inactivity was highest in Bangladesh, followed by Sri Lanka, and India. Surprisingly, Nepal had lowest SRH despite its highest prevalence of MPA and second highest prevalence of VPA. As expected, engaging in regular PA was associated with higher odds of good SRH for most of the countries. In Bangladesh and Nepal, those who participated in MPA on a daily basis, and in Sri Lanka, those took MPA 5-6 days a week, had the highest odds of reporting good SRH. For VPA, highest odds of reporting good SRH were reported among those who exercised on daily basis, compared with those who exercised at a lesser frequency. Among all the countries, the strongest associations between SRH and PA in both categories was observed in Sri Lanka. A major barrier to reporting association between SRH and PA is the lack of comparable studies reporting prevalence at the national level and the absence of standardised and validated instruments in studied countries24. Previous studies based on USA (86.2%)20 and Canada (89.9%)21 concluded that participants who rated their health as poor to average were less likely to take PA compared with those who rated their general health as good to excellent21. Similar findings were observed in South Korea, where an independent association between lower level of PA and poor SRH was reported22. Regarding the prevalence of PA, a study encompassing 76 countries reported that the prevalence of physical inactivity among individuals aged 15 years or older ranged from 3 to 62%23, which varied substantially from the worldwide prevalence of physical inactivity in adults of 31%24. This study has some important limitations. Number of days of VPA and MPA (at least 10 minutes at a time) was used as a proxy for level of PA instead of exact duration. However, similar methodology was used in some other studies21,26. Another limitation is the absence of several necessary covariates which are commonly correlated with the level of PA, such as presence of disease conditions (diseased people are less likely to engage in PA), place of residency (urban and rural residences have differing patterns of engaging in PA), and other community level variables (e.g. neighbourhood cleanliness, safety, availability of public spaces for exercise). As the data were secondary, we had no control over the choice of selecting the covariates and the ways they were measured. For instance, we could not distinguish between work and leisure physical activity, which could have affected the associations. With the data being self-reported, there remains a possibility of under- and over-reporting, as well as the recall bias. Moreover, there are also differences in the way in which men and women describe their health. Women are more likely to report poorer functioning and worse overall health than men27. Last but not least, the results cannot be generalised to all age groups, since no data were available on participants below 18 years of age. Further research is needed to better understand subgroup variations with larger sample sizes to address the heterogeneity found within South Asian groups in this study, who may have different motivations to undertaking and increasing their PA levels. At policy making level, attempts should be taken to encourage PA by improving the provision of necessary infrastructure and environment for exercise. This should be facilitated by developing national PA guidelines for people of different ages. Further studies should investigate the predictive factors of PA in the population and monitor the trends in PA to improve public health. References 1. 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