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Physical activity and sedentary behaviour research in Thailand: a systematic scoping review

Abstract

Background

The number of deaths per year attributed to non-communicable diseases is increasing in low- and middle-income countries, including Thailand. To facilitate the development of evidence-based public health programs and policies in Thailand, research on physical activity (PA) and sedentary behaviour (SB) is needed. The aims of this scoping review were to: (i) map all available evidence on PA and SB in Thailand; (ii) identify research gaps; and (iii) suggest directions for future research.

Methods

A systematic literature search was conducted through 10 bibliographic databases. Additional articles were identified through secondary searches of reference lists, websites of relevant Thai health organisations, Google, and Google Scholar. Studies written in Thai or English were screened independently by two authors and included if they presented quantitative or qualitative data relevant to public health research on PA and/or SB.

Results

Out of 25,007 screened articles, a total of 564 studies were included in the review. Most studies included PA only (80%), 6.7% included SB only, and 13.3% included both PA and SB. The most common research focus was correlates (58.9%), followed by outcomes of PA/SB (22.2%), prevalence of PA/SB (12.4%), and instrument validation (3.2%). Most PA/SB research was cross-sectional (69.3%), while interventions (19.7%) and longitudinal studies (2.8%) were less represented. Most studies (94%) used self-reports of PA/SB, and few (2.5%) used device-based measures. Both sexes were examined in most studies (82.5%). Adults were the main target population group (51.1%), followed by older adults (26.9%), adolescents (15.7%), and children (6.3%). Clinical populations were investigated in the context of PA/SB in a relatively large number of studies (15.3%), most frequently those with cardiovascular disease, diabetes, and hypertension (22%, 21%, and 21% respectively).

Conclusions

The number of Thai papers on PA published per year has been increasing, indicating a growing interest in this research area. More studies using population-representative samples are needed, particularly among children and adolescents, and investigating SB as a health risk factor. To provide stronger evidence on determinants and outcomes of PA/SB, longitudinal studies using standardised measures of PA and SB are required.

Peer Review reports

Background

Deaths caused by non-communicable diseases (NCDs), such as cardiovascular disease and cancer, are common worldwide. Global rates of deaths attributed to NCDs increased from 60% in 2000 to 70% in 2015 [1]. Importantly, the rates of mortality caused by NCDs are increasing faster in low- and middle-income countries than in high-income countries [1]. In Thailand, NCD mortality rates increased from 64% in 2000 to 71% in 2015 [1]. Strong evidence has shown positive impacts of physical activity (PA) on the prevention of NCDs [2,3,4,5]. Some evidence also suggests that excessive sedentary behaviour (SB) (e.g. sitting) may increase the risk of several common NCDs, independently of PA [6]. It should be noted, however, that recent methodological papers questioned the independence of PA and SB, based on the argument that these behaviours are co-dependent parts of a time-use composition [7,8,9]. Nevertheless, the prevalence of physical inactivity, defined as not meeting the recommended level of moderate-to-vigorous physical activity (MVPA) and excessive SB, defined as sitting or reclining with low energy expenditure for more than 7 hours/day, is still high across the world, particularly in middle- and high-income countries [10,11,12]. In 2012, it was estimated that nearly three-quarters of all physical inactivity-related deaths occurred in low- and middle-income countries [13]. In Thailand, it was estimated that 6.3% of total mortality cases could be attributable to physical inactivity in 2013 [14]. Although, no country-specific estimates are available for Thailand, global estimates suggest that excessive SB is responsible for 3.4% of all-cause mortality [12].

Thailand has been affected by urbanisation, where, in search of better socioeconomic opportunities, many young working people move to urban areas or cities, especially to the capital, Bangkok. According to the Department of Economic and Social Affairs, United Nations, half of the Thai population (51.1%) is urban [13]. This increased rapidly from 1955 when only 18% of the Thai population lived in urban areas [13]. Many issues have arisen as a consequence of the increasing number of people living in the urban setting. An emerging concern related to urbanisation is the increasing time spent in SB in Thai population and its negative health outcomes [14]. In Thailand, there has been increasing focus on strategies to improve engagement in PA and reduce SB. Thailand has experienced significant economic development over the past four decades, moving from a low-income to upper-middle income economy [15]. Since 2002, Thailand has established a “Universal Health Coverage” scheme, to provide healthcare and financial protection to all Thai nationals [16].

As part of the national health promotion strategies, the Thai Government has aimed to promote engagement in PA since 1997 and has recently included targets to reduce SB as ways to reduce the burden of NCDs [17]. Moreover, a number of national actions have been taken to help achieve the World Health Organization’s (WHO) 15-year global target, set in 2010, of 10% reduction in the prevalence of physical inactivity, defined as less than 60 minutes of MVPA daily for adolescents and 150 minutes of MVPA weekly for persons aged 18 and over [17, 18]. WHO has commended Thailand as the regional leader in developing national health policies to promote better health through increasing PA [19]. Many PA promoting initiatives and public campaigns were introduced in Thailand, such as the development of new cycle paths, marathons organised all over the country, and a weekly program of aerobic exercise at workplace launched and led by the Prime Minister of Thailand [17, 19, 20]. Further, the national strategies and guidelines for increasing PA and reducing SB were developed [21]. Despite initiatives to increase the Thai population’s engagement in PA, population-based studies suggest that the prevalence of physical inactivity has increased from 18.5% in 2008 [22] to 19.2% in 2014 [23]. This suggests that the development and implementation of effective public health programs and policies to promote PA and decrease SB is needed.

In PA and SB epidemiology, a number of literature reviews have been conducted. For example, reviews have examined worldwide patterns of PA and SB, and show a shift from physically active to sedentary lifestyles [24,25,26]. Other reviews have examined factors associated with PA and SB, and the efficacy of interventions to influence the behaviours, especially in high-income countries [27,28,29,30,31,32,33]. However, most previous literature reviews are restricted to English language studies only and, therefore, studies from many low- and middle-income countries, including Thailand, have typically not been included. Furthermore, many previous reviews on PA and SB are restricted to specific, narrow topics (e.g. environmental determinants of PA) [27]. A comprehensive assessment of epidemiological evidence on PA and SB in the Thai context is lacking. To provide directions for future studies informing public health policies and actions targeted to increase PA and reduce SB, it is important to map the available evidence on epidemiology of PA and SB in Thailand. Scoping reviews have shown to be a useful method for a systematic assessment of the current body of evidence in a broad subject area [34]. In this study, we conducted a systematic scoping review to assess previous Thai PA and SB research, to identify research gaps and provide evidence-based directions for future research on PA and SB in Thailand to guide the development of strategies and policies.

Methods

Search strategy

This scoping review was conducted according to the Guidance for Conducting Systematic Scoping Reviews [35]. It included primary and secondary database searches. The primary literature search was conducted from database inception to September 2016 through the following bibliographic databases: Academic Search Premier; CINAHL; Health Source: Nursing/Academic Edition; MasterFILE Premier; PsycINFO; PubMed/MEDLINE; Scopus; SPORTDiscus; Web of Science (including Science Citation Index Expanded, Social Sciences Citation Index, Arts & Humanities Citation Index, Conference Proceedings Citation Index- Science, and Conference Proceedings Citation Index- Social Science & Humanities); and the Networked Digital Library of Theses and Dissertations (NDLTD). PubMed/MEDLINE, Scopus and Web of Science databases were searched using their own search engines, whilst other databases were searched through EBSCOhost. The search was conducted through titles, abstracts, and keywords of the indexed publications. The detailed search strategies, including the full search syntaxes, used for each database can be found in Additional file 1.

Additional articles and grey literature documents were identified via secondary literature searching through: (i) the reference lists of all articles selected in the primary search; (ii) websites of ten relevant Thai public health institutions and organizations, including the Division of Physical Activity, Ministry of Public Health; Thai Health Promotion Foundation; Physical Activity Research Centre; Health Systems Research Institute; Thai NCD Network; Thai National Research Repository; Thai Thesis Database; and three university sources including Institute for Population and Social Research, Mahidol University; Chulalongkorn University Intellectual Repository; and Kasetsart University Research and (iii) Google and Google Scholar.

Study selection and inclusion criteria

All references from the primary database search were imported in EndNote X7 software (Thompson Reuters, San Francisco, CA, USA). After removing duplicates, the references were screened independently by two authors (NL and KS). The discrepancies between the study selections were resolved in discussion and consensus with a third author (ZP).

Studies were included in the present review, if they: (i) targeted any population group living in Thailand; (ii) conducted research on PA, physical inactivity, and/or SB; (iii) presented any quantitative or qualitative data relevant to public health, including but not limited to the levels, prevalence, correlates, determinants, or outcomes of engagement in PA and/or SB; or described the development or performed an evaluation of a PA and/or SB measurement tool or intervention; (iv) used any type of PA and/or SB measure, such as self-reports or device-based measures; (v) were written in Thai or English; and (vi) published as a journal article, conference paper, conference abstract, Master’s thesis, Doctoral thesis, or report. Studies were excluded, if they: targeted non-Thai populations; had the primary outcome(s) focusing on sports/exercise performance, or physical therapy; and were published as literature reviews, commentaries, and editorials.

Data extraction

The following data were extracted from the included studies: (i) general bibliographical information, including author names, publication year, title, publication type, full text availability, language of full text, abstract availability, and language of abstract; (ii) description of research methods, including study design, survey method, sample size, and sampling method; (iii) information about the study population, including sex, age, municipality (rural/urban), region, and other specific characteristics of participants; (iv) description of measures, including the type of PA/SB measure, device model or questionnaire name, domains included (such as work, transport, and leisure-time), information about whether the measure has been validated or not (if applicable), and intervention type (if applicable); and (v) information about the study objectives. The detailed data extraction table for studies used in the review is available in Additional file 2.

Results

Search results

The flow diagram depicting the search and study selection processes can be found in Fig. 1. A total of 25,007 records were screened for inclusion. Of these, 8,389 studies were identified through primary searches, where, after removing duplicates, the titles and abstracts of 5,875 and full texts of 402 articles were screened. The secondary search yielded 16,618 results, of which 238 articles were selected. Overall, a total of 564 studies were included for review [36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354,355,356,357,358,359,360,361,362,363,364,365,366,367,368,369,370,371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,432,433,434,435,436,437,438,439,440,441,442,443,444,445,446,447,448,449,450,451,452,453,454,455,456,457,458,459,460,461,462,463,464,465,466,467,468,469,470,471,472,473,474,475,476,477,478,479,480,481,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,498,499,500,501,502,503,504,505,506,507,508,509,510,511,512,513,514,515,516,517,518,519,520,521,522,523,524,525,526,527,528,529,530,531,532,533,534,535,536,537,538,539,540,541,542,543,544,545,546,547,548,549,550,551,552,553,554,555,556,557,558,559,560,561,562,563,564,565,566,567,568,569,570,571,572,573,574,575,576,577,578,579,580,581,582,583,584,585,586,587,588,589,590,591,592,593,594,595,596,597,598].

Fig. 1
figure 1

Flow diagram of study selection process

Bibliographic characteristics of included studies

All papers included in this review were published between 1987 and 2016. The number of papers published per year has increased over time (Fig. 2). English was the primary language used in the majority of Thai PA/SB papers full texts (67.4%), whilst nearly all papers (n = 546) had at least an English abstract (Fig. 3). Furthermore, 17% of full-text articles and 10.1% of abstracts were not available online, and, therefore, other means were used to access the publications (e.g. authors’ contacts and request through university libraries). Most studies were peer-reviewed journal articles (68.3%), followed by theses (19.9%), conference papers (6.6%), and reports (5.3%).

Fig. 2
figure 2

The number of Thai studies on physical activity and sedentary behaviour published per year

Fig. 3
figure 3

Languages used in full-texts and abstracts of Thai physical activity and sedentary behaviour publications

Study characteristics

In 363 of 564 included studies (64.4%), PA and/or SB were the primary focus of the research (e.g. a study on correlates of PA), whilst the remaining studies were not strictly focused on PA and/or SB but were analysed among multiple other variables as key explanatory or outcome variables together with PA and/or SB (e.g. other lifestyle characteristics such as smoking). Eighty percent of the studies included PA only, 6.7% included SB only, and 13.3% included both PA and SB. Most studies focused on correlates of PA/SB (58.9%), followed by outcomes of PA/SB (22.2%), prevalence of PA/SB (12.4%), and instrument validation (3.2%). 69.3% of studies used cross-sectional designs. Less represented were intervention trials (19.7%), case-control studies (3.7%), longitudinal studies (2.8%), and measurement studies (2.3%). The majority of studies used quantitative methods (87.9%), with only 4.6% and 7.5% utilising qualitative methods or mixed-methods, respectively. In most studies, the data was collected using self-administered surveys (56.7%) or face-to-face interviews (31.4%) (Fig. 4). The sample sizes of the studies ranged from 6 to 113,882 and 7.8% of the studies were conducted using nationally representative samples. Among the studies in nationally representative samples, 29.5% were secondary data analyses of the following national surveys: National Health Examination Survey; National Elderly Survey; Thailand Global School-Based Student Health Survey; 2007 National Physical Activity and Obesity Survey; and 2010 Evaluation of Health Promotion and Sports in Regions. There were seven government reports on PA and/or SB levels presenting results from population-based studies, such as the Health and Welfare Survey 2015 conducted by the National Statistical Office and National Health Examination Survey conducted by the National Health Examination Survey Office.

Fig. 4
figure 4

Measures of physical activity and sedentary behaviour used in Thai studies

Characteristics of study samples

Participants of both sexes were included in 82.5% of studies. Studies of females only (15.4%) were more common than studies of males only (2.1%). Adults (18-59 years) were the most frequently investigated age group (51.1%), followed by older adults (60+ years; 26.9%), adolescents (10 to 17 years; 15.7%), children (4 to 9 years; 5.4%), and infants/toddlers (0 to 3 years; 0.9%). A large majority of studies were conducted in non-clinical populations (84.7%). Of these, 28.5% were conducted among primary-school, secondary-school, high-school, and university students. Employees in health-related professions, including nurses, physicians, and health-care students such as medical residents were participants in 9.8% of studies. Other specific occupations were represented in 6.5% of studies; most common among them were farmers, military personnel, university staff, and office workers. Some studies (2.1%) were conducted among employees in specific organizations, such as the Electricity Generating Authority of Thailand, Metropolitan Waterworks, and the Teachers Council. Other specific non-clinical populations included in the studies were, for instance, people with low or high level of PA or SB regularity (5.6%), obese/overweight people (3.8%), women before or in menopause (2.9%), pregnant women (1.3%), and tobacco smokers (0.4%). Clinical populations were also examined in the context of PA/SB (17.7%). Patients with cardiovascular disease, diabetes, and hypertension were among the most frequently observed groups (22%, 21%, and 21%, respectively). Hip/knee problems (13%) and cancers (6%) were also clinical conditions of interest (Table 1). By geographical distribution, Bangkok the capital was the most studied area (28.8%) and the Southern region was the least studied area (15.2%).

Table 1 Population groups studied in Thai physical activity and sedentary behaviour research

Measures of physical activity and sedentary behaviour

Out of 526 studies that investigated PA, most relied on self-reports only (73.4%) and 2.1% used both self-report and device-based measures. In nearly all of these studies (97.2%) PA was assessed using self-reported or proxy-reported questionnaires, and in most cases it was not specified which questionnaire or questionnaire item(s) were used for this purpose. The Global Physical Activity Questionnaire (GPAQ) and the International Physical Activity Questionnaire (IPAQ) were used in 25 (6.5%) and 23 studies (6%), respectively. Other self-reports were PA diary and logbook used in 14 studies (3.5%). Device-based measurement was used in 23 studies (4.4%), with accelerometer (n = 10) and pedometer (n = 9) being the most common devices. A large proportion of PA studies focused on exercise only (49.6%) or on total PA (32.5%). Domain-specific PA levels, including leisure-time, household, work-related, and transport PA, were examined in isolation in 2.5% of all PA studies. The most commonly studied domain of PA was leisure time (n = 16). Walking, as a type-specific PA, was investigated independently in 5 studies. In total, 5.9% of studies assessed a combination of domain- and type-specific PA levels, including exercise, sport and walking.

A total of 113 studies examined SB. Questionnaires were the most common measure of SB (91.2%), followed by activity diaries (4.4%), and device-based tools (3.5%). Most studies (65.5%) did not specify which questionnaires they used. GPAQ, IPAQ, and accelerometers were used in eight, four, and two studies, respectively. Screen time - including TV viewing, computer use, videogames, and internet/social networking - was the most commonly investigated type-specific SB (59.3%). Total sedentary or sitting time was assessed in 37 studies (32.7%), while SB in work and leisure-time domains was assessed in seven and five studies respectively.

Study topics

Correlates of PA and/or SB were the most common topic and were investigated in 58.9% of studies. We identified 11 groups of PA/SB correlates. The most common were: socio-demographic correlates, such as, age, gender, and education level (24%); psychological correlates, such as mental health and well-being, self-efficacy, social behaviours, and cognitive tasks (20.9%); physical health and functioning correlates including physiological and biological functions, diseases, and health problems (19.8%); and social and cultural correlates, such as social support, beliefs, and social practices (11.4%). Other reported correlates included: health behaviours and lifestyles; physical environment; general health; physical skills, abilities, and fitness; academic performance; knowledge; and policy (Table 2).

Table 2 Number of studies investigating correlates and outcomes of physical activity and sedentary behaviour in Thai populations

In total, 125 (22.2%) of the selected studies examined outcomes of PA and/or SB. Most of these studies examined physical health and functioning (33.8%), psychological outcomes (21.8%), physical skills, abilities, and fitness (19.4%), and health behaviours and lifestyles (14.8%). Other reported outcomes included general health; mortality; social characteristics; environmental characteristics; and knowledge (Table 2).

A number of measures were tested for validity and reliability in the Thai context (6.7%). These were mostly questionnaires (92.1%) such as GPAQ, IPAQ (short version), Godin-Shephard Leisure-Time Physical Activity Questionnaire (GSLTPAQ), Modifiable Activity Questionnaire for Adolescents (MAQA), and Perceived Benefits to Physical Activity Scale (PBEPAS). Two studies evaluated measurement properties of device-based measures of PA (pedometer and heart rate monitors). In one study [159] the Compendium of Physical Activities [599] was translated and validated.

Discussion

This study is the first systematic scoping review that summarises current evidence of Thai PA and SB research to support national directions in promoting healthy lifestyle through PA. We identified a large number of PA and SB studies conducted in Thailand, covering a broad range of topics, and using a variety of study designs. There was an increase in the number of Thai PA and SB studies published per year, from one study in 1987 to 64 studies in 2015 (the search was conducted up to September 2016), indicating a growing interest in this research area.

The first Thai publication focusing on PA that we identified was a doctoral thesis from 1987 [289], however the vast majority of PA studies were published in the last two decades. Importantly, the number of Thai papers on PA published per year has been increasing (Fig. 2), indicating that this area of research is developing. It is important to note that half of the studies on PA focused on exercise only, overlooking other types of PA (such as occupational PA, household PA, transport-related PA, and leisure-time PA other than exercise). Historically, the terms ‘physical activity’ and ‘exercise’ have been used interchangeably, and exercise has been one of the most commonly studied types of PA [600]. However, exercise is only one out of several various specific types of PA that may be important for health. From the public health perspective, it is important to study not only exercise but also other types of PA. In Thailand, the term “exercise” had been more widely used until the “physical activity” term was formally promoted in 2002, when the national focal point was changed from the Exercise Unit to the Division of Physical Activity and Health [17].

This finding for Thai studies is consistent with global trends in PA research over the last few decades. The proportion of studies using total MVPA (and not just exercise) as a measure of PA has increased in the last decade [49, 67, 230, 231, 432]. To align with Thai national recommendations on total MVPA, this trend in gathering evidence should be continued in future studies. Importantly, we did not locate any Thai population-based study that considered participation in muscle-strengthening activities, which is similar to the situation in most other countries [601, 602]. Given that Thai national PA guidelines for adults include a separate recommendation on participation in muscle-strengthening activities [603], this suggests more studies on this specific type of PA are needed.

Up until the present, studies on SB in Thailand were less represented than those on PA. SB research is a more recent field of inquiry, compared with PA epidemiology. It has only been in the past two decades that SB has been recognised as a risk factor independent of PA level [604,605,606,607]. It was therefore expected that in Thailand SB research would be less developed than PA research. Of the 113 studies addressing SB, 40 looked at specific types of SB, such as TV viewing, computer/internet use, and playing video games. The earliest Thai study we identified that examined type-specific SB, was conducted in 1994, as part of a doctoral thesis focusing on TV viewing and academic achievement [99]. The first study assessing total SB was conducted in 2000, again as part of a doctoral thesis [434]. Since then, there has been a steady increase in the number of Thai papers on SB published per year, indicating an increasing recognition of the importance of this area of research. Given the prevalence of SB and its potential negative health outcomes [6, 12], it is important that future studies continue to focus on SB in Thai populations.

Recent methodological developments have led to the establishment of a new discipline, called time-use epidemiology, where periods of time spent in PA, SB and sleep are no longer considered as independent risk factors, but instead are treated as mutually exclusive and exhaustive parts of the 24-hour day [7,8,9]. The new approach allows for drawing conclusions about how different reallocations of time between PA, SB and sleep affect health, and for finding the optimal balance of these components of time-use for good health [9, 608]. In line with the new developments and with the public health guidelines adopted in other countries [609,610,611], the most recent Thai guidelines on movement/non-movement behaviours included recommendations on PA, SB, and sleep [603]. However, the current review found no Thai studies aligned with this new approach, suggesting that this might be an area worth exploring in future epidemiological studies in Thailand.

Almost 70% of all included studies (PA and SB) used cross-sectional designs, whilst the evidence base on determinants and outcomes of PA/SB from longitudinal studies and intervention trials is less developed, potentially due to affordability-related reasons. However, a limitation of cross-sectional data is that they do not allow to draw conclusions about the direction of analysed relationships. To get a better insight into potential causes and consequences of PA and SB, longitudinal studies and controlled intervention trials are needed. Most studies in Thailand assessed PA and/or SB using self-reports. Despite the limitations of self-report instruments [612], these are still the predominant measure of PA and SB in population-based surveys internationally [613, 614]. The use of device-based measures of PA and SB, such as accelerometers, in large-scale epidemiological studies is becoming more affordable, especially in high-income countries [615,616,617]. However, device-based measurement of PA and/or SB was seldom used in the Thai context. This is likely due to issues related to the high cost and participant burden associated with device-based measurement of PA and SB [614]. Although device-based measuring has limitations in assessing domain- and type-specific PA and SB levels, it may provide some data that cannot be reliably assessed by existing questionnaires (e.g. timing of different activities during a day, detailed data on weekly distribution of PA). To better understand patterns of PA and SB in Thai populations, future research might benefit from employing device-based measures alongside self-report measures.

Although studies included in this review used a variety of sampling methods and a broad range of sample sizes, few were conducted in large-scale population-representative samples. Besides national surveys funded by the Thai government using large scale data samples, such as National Health Examination Survey, Thailand Physical Activity Children Survey, National Physical Activity and Obesity Survey, and Health and Welfare Survey, 10 other studies also utilized a large scale sample (n range: 24,743 – 87,143) from the Sukhothai Thammathirat Open University cohort. To improve the generalisability of findings from observational studies, the use of such large, nationally representative samples should be encouraged in future Thai PA and SB research.

Across age categories, young to middle aged adults (18-59 years) were the most commonly studied population group, followed by older adults (60+ years). The convenience of conducting research among adults and older adults, compared with research among children and adolescents, in terms of ethical considerations, ease of access to participants, and simplicity of measurement, may partially explain why most Thai PA and SB studies focused on these age groups. Another reason may be that adulthood and older age are more convenient stages to observe health impacts of PA and SB, as symptoms of many diseases rarely occur in younger population groups [618]. However, in addition to a number of topics in PA and SB research that are specific for children and adolescent populations (e.g. levels and patterns of school-based PA and SB, tracking of PA and SB from childhood to adolescence, association of PA and SB with educational outcomes in primary and secondary schools, effectiveness of PA and SB interventions in the school setting), findings among adults may not be generalizable to the populations of children and adolescents, which calls for more studies of these age groups in the future.

Thai PA and SB studies covered a wide range of topics, largely consistent with PA/SB research trends in middle- and high-income countries globally [5, 10, 12, 27]. However, there has been limited research on environmental correlates/determinants of PA and SB, associations between PA/SB and mortality outcomes, PA/SB policy research, and validation of device-based measures of PA/SB in different Thai population groups (e.g. across different sociodemographic groups). Around one-third of Thai PA/SB papers were published in the Thai language, while the remaining papers were published in English. Publications in English have higher visibility in the international scholarly context. Alternatively, publications in Thai may better inform local public health stakeholders, media and the general non-academic readership. Ideally, all publications would be in both languages, but in reality this is not feasible. It is, therefore, important to keep a balance between publishing in Thai and English, by always carefully considering the primary purpose of the paper and the targeted readership.

This systematic scoping review has several strengths. First, a systematic search and study selection strategy were applied to identify eligible studies. Comprehensiveness of the search was achieved by using a large number of relevant PA- and SB-related keywords, conducting primary search through 10 bibliographic databases, and supplementing this with an extensive secondary search. Second, data on 39 variables were extracted from the selected studies, which allowed for a detailed interpretation of the current situation in Thai PA and SB research. Last, a key strength was that, since both Thai and English language papers were included, we were able to review a large number of studies that might not have been captured if we only reviewed papers in one language.

This scoping review has some limitations. Although we tried to identify as many studies as possible, we may have missed some studies because they were not indexed in the selected databases. Furthermore, given the large total number of included studies, we focused on providing general recommendations, whilst an in-depth assessment of each individual study was not feasible. Future reviews are needed to summarise findings on specific topics in PA/SB epidemiology within the Thai context, particularly by different age groups (e.g. children, adolescents, adults, and older adults.

Summary recommendations for future research

Based on this systematic scoping review, it can be concluded that the greatest Thai PA/SB research gaps and limitations are: the lack of studies on SB; the use of unspecified and non-validated measures of PA and SB; a limited number of longitudinal studies; a limited number of studies conducted in population-representative samples; a limited number of studies conducted among children and adolescents; a limited coverage of several important PA/SB research topics, such as environmental factors. To provide stronger evidence and further improve the evidence base on PA and SB, future studies may consider several recommendations stemming from this review. First, given that SB research is less developed in the Thai context and that SB is emerging as a new and important health-risk factor among the Thai population [16], more studies on determinants of, outcomes of, and ways to reduce SB in the Thai population are needed. Future studies in Thailand would also be strengthened by using validated device-based and self-report measures of PA and SB. For a better understanding of determinants and outcomes of PA and SB in Thailand, future studies should aim to use longitudinal study designs. Additionally, to allow for better generalisation, more studies should use large, population-representative samples. Besides, future studies are needed specifically focusing on topics relevant to children and adolescents. Finally, research shows that PA is influenced by a number of individual, social, environmental, and policy factors [27, 619]. Whilst socio-demographic, psychological, and social correlates have been the topic of a number of Thai studies, more research is needed on environmental and policy-related correlates of PA and SB in Thailand.

Conclusions

Thai research on PA and SB has rapidly evolved and received increasing attention in the last two decades. Substantial literature was mapped in this review, showing that existing research has a great potential to support the development of healthy lifestyles by increasing PA and reducing SB in Thailand. However, current evidence could be strengthened, particularly by conducting more research on SB, using sound research methods, and covering the full range of research topics on determinants and outcomes of PA and SB. By following the recommendations provided in this systematic scoping review, future studies may provide even stronger evidence needed to inform public health efforts to promote PA and reduce SB in Thailand.

Abbreviations

GPAQ:

Global Physical Activity Questionnaire

GSLTPAQ:

Godin-Shephard Leisure-Time Physical Activity Questionnaire

IPAQ:

International Physical Activity Questionnaire

MAQA:

Modifiable Activity Questionnaire for Adolescents

MVPA:

Moderate-to-Vigorous Physical Activity

NCDs:

Non-Communicable Diseases

NDLTD:

Networked Digital Library of Theses and Dissertations

PA:

Physical Activity

PBEPAS:

Perceived Benefits to Physical Activity Scale

SB:

Sedentary Behaviour

WHO:

World Health Organization

References

  1. The World Bank: WHO's World Health Statistics. http://data.worldbank.org/indicator/SH.DTH.NCOM.ZS. Accessed 9 Jan 2017.

  2. World Health Organization. Global recommendations on physical activity for health. Geneva: World Health Organization; 2010.

    Google Scholar 

  3. Miles L. Physical activity and health. British Nutrition Foundation Nutrition Bulletin. 2007;32:314–63.

    Article  Google Scholar 

  4. Warburton DE, Charlesworth S, Ivey A, Nettlefold L, Bredin SS. A systematic review of the evidence for Canada’s Physical Activity Guidelines for Adults. Int J Behav Nutr Phys Act. 2010;7:39.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Lee I-M, Shiroma EJ, Lobelo F, Puska P, Blair SN, Katzmarzyk PT. Lancet Physical Activity Series Working Group. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. 2012;380:219–29.

    Article  PubMed  PubMed Central  Google Scholar 

  6. de Rezende LFM, Lopes MR, Rey-Loṕez JP, Matsudo VKR, Luiz ODC. Sedentary behavior and health outcomes: An overview of systematic reviews. PLoS ONE. 2014; https://doi.org/10.1371/journal.pone.0105620.

  7. Pedišić Ž. Measurement issues and poor adjustments for physical activity and sleep undermine sedentary behaviour research: The focus should shift to the balance between sleep, sedentary behaviour, standing and activity. Kinesiol. 2014;46(1):135–46.

    Google Scholar 

  8. Dumuid D, Stanford TE, Martin-Fernandez JA, Pedišić Ž, Maher CA, Lewis LK, et al. Compositional data analysis for physical activity, sedentary time and sleep research. Statistical Methods in Medical Research. 2017; https://doi.org/10.1177/0962280217710835.

  9. Pedišić Ž, Dumuid D, Olds T. Integrating sleep, sedentary behaviour, and physical activity research in the emerging field of time-use epidemiology: definitions, concepts, statistical methods, theoretical framework, and future directions. Kinesiol. 2017;49(2):1–18.

    Article  Google Scholar 

  10. Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U. Lancet Physical Activity Series Working Group. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet. 2012; https://doi.org/10.1016/S0140-6736(12)60646-1. PMID:22818937

  11. Dumith SC, Hallal PC, Reis RS, Kohl HW III. Worldwide prevalence of physical inactivity and its association with human development index in 76 countries. Prev Med. 2011;53:24–8.

    Article  PubMed  Google Scholar 

  12. LFM d R, de Sá TH, Mielke GI, Viscondi JYK, Rey-López JP, Garcia LMT. All-cause mortality attributable to sitting time: Analysis of 54 countries worldwide. Am J Prev Med. 2016; https://doi.org/10.1016/j.amepre.2016.01.022.

  13. Worldometers: Thailand population. Elaboration of data by United Nations, Department of Economic and Social Affairs, Population Division. World Population Prospects: The 2015 Revision. http://www.worldometers.info/world-population/thailand-population/ (2015). Accessed 17 Jan 2017.

  14. Ketwongsa P. Physical activity survey of Thailand 2015. Nakornpathom: Population and Social Research Institute, Mahidol University; 2015. (in Thai).

    Google Scholar 

  15. The World Bank: The World Bank in Thailand. http://www.worldbank.org/en/country/thailand/overview. Accessed 17 Jan 2017.

  16. Centre for Global Development: Thailand’s Universal Coverage Scheme. http://millionssaved.cgdev.org/case-studies/thailands-universal-coverage-scheme. Accessed 17 Jan 2017.

  17. Topothai T, Chandrasiri O, Liangruenrom N, Tangcharoensathien V. Renewing commitments to physical activity targets in Thailand. The Lancet comment. 2016;388(10051):1258–60.

    Article  Google Scholar 

  18. World Health Organization. NCD global monitoring framework. Geneva: World Health Organization; 2013. http://www.who.int/nmh/global_monitoring_framework/en/. Accessed 22 Jan 2017

    Google Scholar 

  19. World Health Organization. Thailand’s physical activity drive is improving health by addressing NCDs. 2017. http://www.who.int/en/news-room/feature-stories/detail/thailand-s-physical-activity-drive-is-improving-health-by-addressing-ncds. Accessed 2 May 2018.

    Google Scholar 

  20. Katewongsa P, Sawangdee Y, Yousomboon C, Choolert P. Physical activity in Thailand: The general situation at national level. J Sci Med Sport. 2014;18:e100–e1.

    Article  Google Scholar 

  21. Division of Physical Activity and Health. Department of Health. Physical activity guideline for Thai people. Nonthaburi: Ministry of Public Health; 2016.

    Google Scholar 

  22. Office of National Health Examination Survey. National Health Examination Survey 2008. Bangkok: Ramathibodi Hospital; 2008. in Thai

    Google Scholar 

  23. Office of National Health Examination Survey. National Health Examination Survey 2014. Bangkok: Health System Research Institute; 2016. in Thai

    Google Scholar 

  24. Ng SW, Popkin BM. Time use and physical activity: a shift away from movement across the globe. Obes Rev. 2012;13(8):659–80.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Katzmarzyk PT, Mason C. The physical activity transition. J Phys Act Health. 2009;6(3):269–80.

    Article  PubMed  Google Scholar 

  26. Knuth AG, Hallal PC. Temporal Trends in Physical Activity: A Systematic Review. J Phys Act Health. 2009;6:548–59.

    Article  PubMed  Google Scholar 

  27. Bauman AE, Reis RS, Sallis JF, Wells JC, Loos RJF, Martin BW. Lancet Physical Activity Series Working Group. Correlates of physical activity: why are some people physically active and others not? Lancet. 2012;380:258–71.

    Article  PubMed  Google Scholar 

  28. Sallis JF, Prochaska JJ, Taylor WC. A review of correlates of physical activity of children and adolescents. Med. Sci. Sports Exerc. 2000;32(5):963–75.

    Article  PubMed  CAS  Google Scholar 

  29. Trost SG, Owen N, Bauman AE, Sallis JF, Brown W. Correlates of adults’ participation in physical activity: review and update. Med. Sci. Sports Exerc. 2002;34(12):1996–2001.

  30. Rhodes RE, Mark RS, Temmel CP. Adult sedentary behavior: a systematic review. Am J Prev Med. 2012;42(3):e3–28.

    Article  PubMed  Google Scholar 

  31. Pearson N, Biddle SJH. Sedentary Behavior and Dietary Intake in Children, Adolescents, and Adults: A Systematic Review. Am J Prev Med. 2011;41(2):178–88.

    Article  PubMed  Google Scholar 

  32. Mabry R, Koohsari MJ, Bull FC, Owen N. A systematic review of physical activity and sedentary behaviour research in the oil-producing countries of the Arabian Peninsula. BMC Public Health. 2016; https://doi.org/10.1186/s12889-016-3642-4.

  33. Schoeppe S, Alley S, Lippevelde WV, Bray NA, Williams SL, Duncan MJ, et al. Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review. Int J Behav Nutr Phys Act. 2016; https://doi.org/10.1186/s12966-016-0454-y.

  34. Arksey H, O'Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Method. 2005;8(1):19–32.

    Article  Google Scholar 

  35. Peters MD, Godfrey CM, Khalil H, McInerney P, Parker D, Soares CB. Guidance for conducting systematic scoping reviews. Int J Evid-Based Healthc. 2015;13(3):141–6.

    Article  PubMed  Google Scholar 

  36. A-piwong C. Exercise behaviors of students at university of the Thai Chamber of Commerce. Bangkok: Graduate School, Srinakharinwirot University; 2011.

    Google Scholar 

  37. Adulyanon S, Vourapukjaru J, Sheiham A. Oral impacts affecting daily performance in a low dental disease Thai population. Community Dent Oral Epidemiol. 1996;24(6):385–9.

    Article  PubMed  CAS  Google Scholar 

  38. Aekplakorn W, Satheannoppakao W, Putwatana P, Taneepanichskul S, Kessomboon P, Chongsuvivatwong V, et al. Dietary Pattern and Metabolic Syndrome in Thai Adults. J Nutr Metab. 2015;2015:1–10.

    Article  Google Scholar 

  39. Ahmed SM, Hadi A, Razzaque A, Ashraf A, Juvekar S, Ng N, et al. Clustering of chronic non-communicable disease risk factors among selected Asian populations: levels and determinants. Global Health Action. 2009;2:68–75.

    Article  Google Scholar 

  40. Akkayagorn L, Tangwongchai S, Worakul P. Cognitive profiles, hormonal replacement therapy and related factors in Thai menopausal women. Asian Biomedicine. 2009;3(4):439–44.

    Google Scholar 

  41. Amini M, Alavi-Naini A, Doustmohammadian A, Karajibani M, Khalilian A, Nouri-Saeedloo S, et al. Childhood obesity and physical activity patterns in an urban primary school in Thailand. Rawal Med J. 2009;34(2):203–6.

    Google Scholar 

  42. Amitrapai Y. Effect of exercise programs on weight and health related fitness of Prathom Suksa 5-6 level over nutritional status students in Banbanglen School, Banglen district, Nakhonpathom province. Nakhon Pathom: Faculty of Graduate Studies, Mahidol University; 2007.

    Google Scholar 

  43. Amnatsatsue K. Measurement of physical function in Thai older adults. Chapel Hill: University of North Carolina; 2002.

    Google Scholar 

  44. Amornsriwatanakul A, Nakornkhet K, Katewongsa P, Choosakul C, Kaewmanee T, Konharn K, et al. Results from Thailand’s 2016 Report Card on Physical Activity for Children and Youth. J Phys Act Health. 2016;13(11 Suppl 2):S291–S8.

    Article  PubMed  Google Scholar 

  45. Andrews A. Factors affecting adult obesity in a large city in Thailand. US: ProQuest Information & Learning; 2014.

    Google Scholar 

  46. Anek A, Bunyaratavej N. Effects of circuit aerobic step exercise program on musculoskeletal for prevention of falling and enhancement of postural balance in postmenopausal women. J Med Assoc Thailand. 2015;98:S88–94.

    Google Scholar 

  47. Anek A, Kanungsukasem V, Bunyaratavej N. Effects of aerobic step combined with resistance training on biochemical bone markers, health-related physical fitness and balance in working women. J Med Assoc Thailand. 2015;98:S42–51.

    Google Scholar 

  48. Angkurawaranon C, Lerssrimonkol C, Jakkaew N, Philalai T, Doyle P, Nitsch D. Living in an urban environment and non-communicable disease risk in Thailand: Does timing matter? Health Place. 2015;33:37–47.

    Article  PubMed  Google Scholar 

  49. Ar-Yuwat S, Clark MJ, Hunter A, James KS. Determinants of physical activity in primary school students using the health belief model. J Multidiscip Healthc. 2013;6:119–26.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Aree P, Wangsrikhun S, Kantawang S, Boonyasopun U, Phienchai K, Buranapin S, et al. Nutritional status, food consumption, and physical activity in adolescents: a pilot study. Nurs J. 2007;34(2):98–105.

    Google Scholar 

  51. Aree-Ue S, Petlamul M. Osteoporosis Knowledge, Health Beliefs, and Preventive Behavior: A Comparison between Younger and Older Women Living in a Rural Area. Health Care Women Int. 2013;34(12):1051–66.

    Article  PubMed  Google Scholar 

  52. Aree-Ue S, Pothiban L. Osteoporosis knowledge, osteoporosis prevention behavior, and bone mass in older adults living in Chiang Mai. Thai J Nurs Res. 2003;7(1):1–11.

    Google Scholar 

  53. Aree-Ue S, Pothiban L, Belza B. Join the Movement to Have Healthy Bone Project (JHBP): Changing behavior among older women in Thailand. Health Care Women Int. 2005;26(8):748–60.

    Article  PubMed  Google Scholar 

  54. Artitdit P, Iamopas O, Bhakta D. Effect of Dietary and Physical Activity Intervention in Overweight and Obese Thai Adults. Ann Nutr Metab. 2013;63:1152.

    Google Scholar 

  55. Asawachaisuwikrom W. Physical activity and its predictors among older Thai adults. J Sci, Technol Human. 2003;1(1):65–76.

    Google Scholar 

  56. Asawachaisuwikrom W. Factors influencing physical activity among older adults in Saensuk sub-district, Chonburi Province. Chonburi: Faculty of Nursing, Burapha University; 2004.

    Google Scholar 

  57. Assantachai P, Maranetra N. Nationwide Survey of the Health Status and Quality of Life of Elderly Thais Attending Clubs for the Elderly. J Med Assoc Thai. 2003;86(10):938–46.

    PubMed  Google Scholar 

  58. Assantachai P, Sriussadaporn S, Thamlikitkul V, Sitthichai K. Body composition: Gender-specific risk factor of reduced quantitative ultrasound measures in older people. Osteoporos Int. 2006;17(8):1174–81.

    Article  PubMed  CAS  Google Scholar 

  59. Atchara P, Kasem N, Mayuree T, Suporntip P, Seabra A, Carvalho J. Associations between Physical Activity, Functional Fitness, and Mental Health among Older Adults in Nakornpathom, Thailand. Asian J Exerc Sports Sci. 2014;11(2):25–35.

    Google Scholar 

  60. Aung MN, Lorga T, Srikrajang J, Promtingkran N, Kreuangchai S, Tonpanya W, et al. Assessing awareness and knowledge of hypertension in an at-risk population in the Karen ethnic rural community, Thasongyang, Thailand. Int J Gen Med. 2012;5:553–61.

    Article  PubMed  Google Scholar 

  61. Aungsusuknarumol C. Exercise for health behavior of community college students in Northern colleges of physical education. Bangkok: Graduate School, Srinakharinwirot University; 2000.

    Google Scholar 

  62. Aunprom-me S, Aunprom-me S. Self-efficacy, decisional balance, and stages of change in physical activity among first year nursing students. J Nurses Assoc Thai, North-Eastern Division. 2012;3(4):22–9.

    Google Scholar 

  63. Aunprom-me S, Aunprom-me S, editors. Physical Activity in Graduating Fourth Year Nursing Students: A comparative study using the Transtheoretical Model and the Stages of Change. Bangkok: ANPOR Conference Bangkok 2015; 2015.

    Google Scholar 

  64. Auvichayapat P, Prapochanung M, TunkamnerdThai O, B-o S, Auvichayapat N, Thinkhamrop B, et al. Effectiveness of green tea on weight reduction in obese Thais: A randomized, controlled trial. Physiol Behav. 2008;93(3):486–91.

    Article  PubMed  CAS  Google Scholar 

  65. Awikunprasert C, Vongjaturapat N, Li F, Sittiprapaporn W. Therapeutic use of music and exercise program on the quality of life in Thai cancer patients. Res J Applied Sci. 2012;7(6):297–300.

    Google Scholar 

  66. Ayudthaya WCN, Kritpet T. Effects of low impact aerobic dance and fitball training on bone resorption and health-related physical fitness in Thai working women. J Med Assoc Thai. 2015;98:S52–S7.

    Google Scholar 

  67. Baiya N, Tiansawad S, Jintrawet U, Sittiwangkul R, Pressler SJA. Correlational Study of Physical Activity Comparing Thai Children With and Without Congenital Heart Disease. Pacific Rim Int J Nurs Res. 2014;18(1):29–41.

    Google Scholar 

  68. Bandasak R, Narksawat K, Tangkanakul C, Chinvarun Y, Siri S. Association between hypertension and stroke among Young Thai adults in Bangkok, Thailand. Southeast Asian J Trop Med Public Health. 2011;42(5):1241–8.

    PubMed  Google Scholar 

  69. Banks E, Lim L, Seubsman SA, Bain C, Sleigh A. Relationship of obesity to physical activity, domestic activities, and sedentary behaviours: Cross-sectional findings from a national cohort of over 70,000 Thai adults. BMC Public Health. 2011;11(1):762.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Banwell C, Lim L, Seubsman SA, Bain C, Dixon J, Sleigh A. Body mass index and health-related behaviours in a national cohort of 87 134 Thai open university students. J Epidemiol Community Health. 2009;63(5):366–72.

    Article  PubMed  CAS  Google Scholar 

  71. Bhoopat L, Rojnuckarin P, Hiransuthikul N, Intragumtornchai T. Low vegetable intake is strongly associated with venous thromboembolism in Thai population. Blood Coagul Fibrinolysis. 2010;21(8):758–63.

    PubMed  CAS  Google Scholar 

  72. Bhuripanyo K, Mahanonda N, Leowattana W, Ruangratanaamporn O, Sriratanasathavorn C, Chotinaiwattarakul C, et al. A 5-year prospective study of conventional risk factors of coronary artery disease in Shinawatra employees: A preliminary prevalence survey of 3,615 employees. J Med Assoc Thai. 2000;83(SUPPL. 2):S98–S105.

    PubMed  Google Scholar 

  73. Binhosen V, PanuThai S, Srisuphun W, Chang E, Sucamvang K, Cioffi J. Physical activity and health related quality of life among the urban Thai elderly. Thai J Nurs Res. 2003;7(4):231–43.

    Google Scholar 

  74. Boonchuaykuakul J. Effectiveness of applying the transtheoretical model to improve physical activity behavior of university students. Oregon: Oregon State University; 2005.

    Google Scholar 

  75. Boonkwamdee S. A study of health behavior of overweight persons in Bangkok Metropolis. Nakhon Pathom: Faculty of Graduate Studies, Mahidol University; 1998.

    Google Scholar 

  76. Boonrat N. Relationships among personal factors, spouse support, and physical activity of postpartum women. Bangkok: Faculty of Nursing, Chulalongkorn University; 2004.

    Google Scholar 

  77. Boonrin P, Choeychom S, Nantsupawat W. Predictive factors on exercise behaviors of nursing students. J Nurs Health Care. 2015;33(2):176–86.

    Google Scholar 

  78. Boonyaratavej N, Suriyawongpaisal P, Takkinsatien A, Wanvarie S, Rajatanavin R, Apiyasawat P. Physical activity and risk factors for hip fractures in Thai women. Osteoporos Int. 2001;12(3):244–8.

    Article  PubMed  CAS  Google Scholar 

  79. Buarapha S. Relationships between personal factors, perception of symptoms severity, self-efficacy, social support, and physical activity in patients with chronic heart failure. Bangkok: Faculty of Nursing, Chulalongkorn University; 2004.

    Google Scholar 

  80. Bunprajun T, Henriksen TI, Scheele C, Pedersen BK, Green CJ. Lifelong Physical Activity Prevents Aging-Associated Insulin Resistance in Human Skeletal Muscle Myotubes via Increased Glucose Transporter Expression. PLoS ONE. 2013;8(6):1–10.

    Article  CAS  Google Scholar 

  81. Buranruk O. Effect of chi-kung exercise on chest expansion and lung volume in elderly people. KKU Res J. 2000;5(1):18–25.

    Google Scholar 

  82. Buranruk O, Eungpinitpong W. Effects of Ruesidadton, Chikung, and combination exercises on stress and quality of life in sedentary women. J Med Technol Phys Ther. 2013;25(3):280–8.

    Google Scholar 

  83. Buranruk O, La Grow S, Ladawan S, Makarawate P, Suwanich T, Leelayuwat N. Thai yoga as an appropriate alternative physical activity for older adults. Journal of Complementary and Integrative Medicine. 2010;7(1):1–14.

    Article  Google Scholar 

  84. Butraprom C. Factors affecting internet addiction behavior of adolescence in Bangkok Metropolis. Bangkok: Faculty of Political Science, Chulalongkorn University; 2002.

    Google Scholar 

  85. Chadchavalpanichaya N, Intaratep N. Exercise behavior and knowledge among the DM type II patients. J Med Assoc Thai. 2010;93(5):587–93.

    PubMed  Google Scholar 

  86. Chanavirut R, Khaidjapho K, Jaree P, Pongnaratorn P. Yoga exercise increases chest wall expansion and lung volumes in young healthy Thais. Faseb J. 2006;20(5):A1257–A.

    Google Scholar 

  87. Chanchalor S. Online games and Thai youth case studies of impact. Soc Sci (Pakistan). 2013;8(2):129–34.

    Google Scholar 

  88. Chanruengvanich W, Kasemkitwattana S, Charoenyooth C, Towanabut S, Pongurgsorn C. RCT: self-regulated exercise program in transient ischemic attack and minor stroke patients. Thai J Nurs Res. 2006;10(3):165–79.

    Google Scholar 

  89. Chansarn S. Active ageing of elderly people and its determinants: Empirical evidence from Thailand. Asia-Pac Soc Sci Rev. 2012;12(1):1–18.

    Google Scholar 

  90. Charoenkitkarn V. The study of perceived self-efficacy and interpersonal influences to exercise behavior in the elderly with essential hypertension. Nakhon Pathom: Faculty of Graduate Studies, Mahidol University; 2000.

    Google Scholar 

  91. Charoensook K. Factors affecting exercise behaviors of teachers in Nakhonpanom province in academic year 2007. Bangkok: Graduate School, Srinakharinwirot University; 2007.

    Google Scholar 

  92. Charoenying W, Asawachaisuwikrom W, Junprasert S. Factors affecting exercise behavior of upper secondary level school students in schools upper the office of Prachinburi educational service area. J Fac Nurs Burapha Univ. 2006;11(1):23–34.

    Google Scholar 

  93. Charupash R. The self care behaviors of the western son's in laws Isaan's rural of Thailand. 7th World Conference on Educational Sciences. Procedia Soc Behav Sci. 2015;197:2310–4.

    Article  Google Scholar 

  94. Chawla N, Panza A. Assessment of childhood obesity and overweight in Thai children grade 5-9 in BMA bilingual schools, Bangkok, Thailand. J Health Res. 2012;26(6):317–22.

    Google Scholar 

  95. Chidnok W, Weerapun O, Srirung T, Pacharean R. Permsuwan A. the study of types and obstacle of exercise in personals of Naresuan University. J Sports Sci Technol. 2007;7(1 and 2):101–8.

    Google Scholar 

  96. Chidnok W, Wiangkham T, Pukyod N, Nitikul P, Inchom A. The study on information of exercise services requirement in students of Naresuan University. J Sports Sci Technol. 2008;8(1):131–41.

    Google Scholar 

  97. Chinuntuya P. A causal model of exercise behavior of the elderly in Bangkok metropolis. Bangkok: Faculty of Graduate Studies, Mahidol University; 2001.

    Google Scholar 

  98. Chirawatkul S. Alternative health used among menopausal women in the northeast of Thailand. 9th International Menopause Society World Congress on the Menopause; 1999. p. 21–5.

    Google Scholar 

  99. Chompaisal S. The perceived influence of television on achievement in children and adolescents in Thailand. Illinois: the United States: Department of Educational Administrational and Foundations, Illinois State University; 1994.

    Google Scholar 

  100. Chonchaiya W, Nuntnarumit P, Pruksananonda C. Comparison of television viewing between children with autism spectrum disorder and controls. Acta Paediatrica. 2011;100(7):1033–7.

    Article  PubMed  Google Scholar 

  101. Chonchaiya W, Pruksananonda C. Television viewing associates with delayed language development. Acta Paediatrica. 2008;97(7):977–82.

    Article  PubMed  Google Scholar 

  102. Chongwatpol P, Gates GE. Differences in body dissatisfaction, weight-management practices and food choices of high-school students in the Bangkok metropolitan region by gender and school type. Public Health Nutr. 2016;19(7):1222–32.

    Article  PubMed  Google Scholar 

  103. Choosakul C, Taweesuk D, Piyasuwan S. The Influence of personal characteristics, behavior specific-cognitions and psychological factors on exercise commitment of Thai adult populations in the Northeast. Int J Psychol. 2008;43(3-4):133.

    Google Scholar 

  104. Chotibang J, Fongkaew W, Mo-suwan L, Meininger JC, Klunklin P. Development of a family and school collaborative (FASC) Program to promote healthy eating and physical activity among school-age children. Thai J Nurs Res. 2009;13(2):133–46.

    Google Scholar 

  105. Chotikacharoensuk P. Physical activity and psychological well-being among the elderly. Chiang Mai: Graduate School, Chiang Mai University; 2002.

    Google Scholar 

  106. Chuamoor K, Kaewmanee K, Tanmahasamut P. Dysmenorrhea among Siriraj nurses; Prevalence, quality of life, and knowledge of management. J Med Assoc Thai. 2012;95(8):983–91.

    PubMed  Google Scholar 

  107. Chukumnerd P, Hatthakit U, Chuaprapaisilp A. The experience of persons with allergic respiratory symptoms: practicing yoga as a self-healing modality. Holist Nurs Pract. 2011;25(2):63–70.

    Article  PubMed  Google Scholar 

  108. Churangsarit S, Chongsuvivatwong V. Spatial and social factors Associated with transportation and recreational physical activity among adults in Hat Yai city, Songkhla, Thailand. J Phys Act Health. 2011;8(6):758–65.

    Article  PubMed  Google Scholar 

  109. Churproong S, Khampirat B, Ratanajaipan P, Tattathongkom P. The effect of the arm swing on the heart rate of non-athletes. J Med Associ Thai. 2015;98:S79–86.

    Google Scholar 

  110. Dajpratham P, Chadchavalpanichaya N. Knowledge and practice of physical exercise among the inhabitants of Bangkok. J Med Assoc Thai. 2007;90(11):2470–6.

    PubMed  Google Scholar 

  111. Dancy C, Lohsoonthorn V, Williams MA. Risk of dyslipidemia in relation to level of physical activity among Thai professional and office workers. Southeast Asian J Trop Med Public Health. 2008;39(5):932–41.

    PubMed  Google Scholar 

  112. Danyuthasilpe C, Amnatsatsue K, Tanasugarn C, Kerdmongkol P, Steckler AB. Ways of healthy aging: A case study of elderly people in a Northern Thai village. Health Promot Int. 2009;24(4):394–403.

    Article  PubMed  Google Scholar 

  113. Daraha K. The effect of the Internet use on high school students: A case study of Pattani province of Thailand. Psu-Usm International Conference on Humanities and Social Sciences. Procedia Soc Behav Sci. 2013;91:241–56.

    Article  Google Scholar 

  114. Dasa P. Exercise behaviors and perceived barriers to exercise among female faculty members in Chiang Mai University. Chiang Mai: Graduate School, Chiang Mai University; 2001.

    Google Scholar 

  115. Decharat S, Phethuayluk P, Maneelok S. Prevalence of Musculoskeletal Symptoms among Dental Health Workers, Southern Thailand. Adv Prev Med. 2016;2016:1–6.

    Article  Google Scholar 

  116. Dedkhard S. Risk factors of cardiovascular disease in rural Thai women. PhD [dissertation]. Arizona: University of Arizona; 2006.

  117. Deenan A. A Comparative Study of Exercise Behaviors, Eating Behaviors, Serum Lipids, and Body Mass Index of Thai Adolescents: Urban and Rural Areas of the Eastern Seaboard of Thailand. Chonburi: Faculty of Nursing, Burapha University; 2001.

    Google Scholar 

  118. Deenan A. Testing the health promotion model with Thai adolescents. PhD [dissertation]. Missouri: Saint Louis University; 2003.

  119. Deesomboon S. The home-based physical activities program in daily life among older adults. Bangkok: Faculty of Graduate Studies, Mahidol University; 2008.

    Google Scholar 

  120. Dennerstein L, Lehert P, Heinemann K. Global study of women's experiences of premenstrual symptoms and their effects on daily life. Menopause Int. 2011;17(3):88–95.

    Article  PubMed  Google Scholar 

  121. Duangchan P, Yoelao D, Macaskill A, Intarakamhang U, Suprasonsin C. Interventions for healthy eating and physical activity among obese elementary schoolchildren: observing changes of the combined effects of behavioral models. Int J Behav Sci. 2010;5(1):46–59.

    Google Scholar 

  122. Duangtep Y, Narksawat K, Chongsuwat R, Rojanavipart P. Association between an unhealthy lifestyle and other factors with hypertension among hill tribe populations of Mae Fah Luang district, Chiang Rai Province, Thailand. Southeast Asian J Trop Med Public Health. 2010;41(3):726–34.

    PubMed  Google Scholar 

  123. Eiamudomkan M, Sirirassamee T, Sirirassamee B. Consumption of vegetables, fruits, physical activity, and sedentary behaviors in Thai adolescents. J Med Health Sci. 2014;21(2):40–8.

    Google Scholar 

  124. Ekpanyaskul C, Sithisarankul P, Wattanasirichaigoon S. Overweight/obesity and related factors among Thai medical students. Asia-Pac J Public Health. 2013;25(2):170–80.

    Article  PubMed  Google Scholar 

  125. Ethisan P, Chapman R, Kumar R, Somrogthong R. Effectiveness of group-mediated lifestyle physical activity program for health benefit in physical activity among elderly people at rural Thailand. Journal Ayub Med Col, Abbottabad: JAMC. 2015;27(2):292–5.

    Google Scholar 

  126. Ethisan P, Somrongthong R, Ahmed J, Kumar R, Chapman RS. Factors Related to Physical Activity Among the Elderly Population in Rural Thailand. J Prim Care Community Health. 2016;8(2):71–76.

    Article  PubMed  PubMed Central  Google Scholar 

  127. Fuangswasdi S. Need for exercising of personnel of the department of Foreign Ministry of Commerce. Bangkok: Graduate School, Ramkhamhaeng University; 1998.

    Google Scholar 

  128. Fuzhong L, Harmer P, Fisher KJ, Junheng X, Fitzgerald K, Vongjaturapat N. Tai Chi-Based Exercise for Older Adults With Parkinson's Disease: A Pilot-Program Evaluation. J Aging Phys Act. 2007;15(2):139–51.

    Article  Google Scholar 

  129. Geurgoolgitjagan N, Chongchareon W. Factors influencing Tai Chi-Chigong exercise by people in Southern Thailand. Songkla: Faculty of Nursing, Prince of Songkla University; 2008.

    Google Scholar 

  130. Gidlöf L, Retta Belay H. Habits related to television, computer games and eating among school children in a rural and an urban area of Thailand. Uppsala: Uppsala University; 2011.

    Google Scholar 

  131. Halvorsen A. Facebook usage in Thailand: The plurilingual competencies of Thai high school students and teachers. US: ProQuest Information & Learning; 2015.

    Google Scholar 

  132. Hamirattisai T, Johnson RA, Kawinwonggowit V. Evaluating functional activity in older Thai adults. Rehabil Nurs. 2006;31(3):124–8.

    Article  Google Scholar 

  133. Harnirattisai T, Johnson RA. Effectiveness of a behavioral change intervention in Thai elders after knee replacement. Nurs Res. 2005;54(2):97–107.

    Article  PubMed  Google Scholar 

  134. Henry CJ, Webster-Gandy J, Varakamin C. A comparison of physical activity levels in two contrasting elderly populations in Thailand. Am J Hum Biol. 2001;13(3):310–5.

    Article  PubMed  CAS  Google Scholar 

  135. Hirohide Y, Motoyuki Y, Nedsuwan S, Moolphate S, Hiroshi F, Tsutomu K, et al. Daily salt intake estimated by overnight urine collections indicates a high cardiovascular disease risk in Thailand. Asia Pac J Clin Nutr. 2016;25(1):39–45.

    Google Scholar 

  136. Hiruntrakul A, Nanagara R, Emasithi A, Borer K. Effect of once a week endurance exercise on fitness status in sedentary subjects. J Med Assoc Thai. 2010;93(9):1070–4.

    PubMed  Google Scholar 

  137. Hiruntrakul A, Nanagara R, Emasithi A, Borer KT. Effect of endurance exercise on resting testosterone levels in sedentary subjects. Cent Eur J Public Health. 2010;18(3):169–72.

    Article  PubMed  CAS  Google Scholar 

  138. Howteerakul N, Suwannapong N, Rittichu C, Rawdaree P. Adherence to regimens and glycemic control of patients with type 2 diabetes attending a tertiary Hospital Clinic. Asia-Pac J Public Health. 2007;19(1):43–9.

    Article  PubMed  CAS  Google Scholar 

  139. Howteerakul N, Suwannapong N, Sittilerd R, Rawdaree P. Health risk behaviors, awareness, treatment and control of hypertension among rural community people in Thailand. Asia-Pac J Public Health. 2006;18(1):3–9.

    Article  PubMed  CAS  Google Scholar 

  140. Howteerakul N, Suwannapong N. Than M. Cigarette, alcohol use and physical activity among Myanmar youth workers, Samut Sakhon Province, Thailand. Southeast Asian J Trop Med Public Health. 2005;36(3):790–6.

    PubMed  CAS  Google Scholar 

  141. In-Iw S, Manaboriboon B, Chomchai C. A comparison of body-image perception, health outlook and eating behavior in mildly obese versus moderately-to-severely obese adolescents. J Med Assoc Thai. 2010;93(4):429–35.

    PubMed  Google Scholar 

  142. In-iw S, Suchritpongsa S, Manaboriboon B, Chomchai C. Obesity in Thai adolescents: lifestyles, health attitudes and psychosocial concerns. Siriraj Med J. 2010;62(6):245–9.

    Google Scholar 

  143. Ing-Arahm R, Suppuang A, Imjaijitt W. The study of medical students’ attitudes toward exercise for health promotion in Phramongkutklao College of Medicine. J Med Assoc Thai = Chotmaihet thangphaet. 2010;93(Suppl 6):S173–8.

    PubMed  Google Scholar 

  144. Insawang T, Selmi C, Cha'on U, Pethlert S, Yongvanit P, Areejitranusorn P, et al. Monosodium glutamate (MSG) intake is associated with the prevalence of metabolic syndrome in a rural Thai population. Nutr Metab. 2012;9:1–6.

    Article  CAS  Google Scholar 

  145. Intachat N. The Influence of Bio-Sociology and Behavioral Factors on Thai Adult Mortality in the Northeastern Community of Thailand. Crisis Management in the Time of Changing World. Adv Intell Syst Res. 2012;63:365–74.

    Google Scholar 

  146. Intarakamhang P, Chintanaprawasee P. Effects of Dao De Xin Xi exercise on balance and quality of life in Thai elderly women. Glob J Health Sci. 2012;4(1):237–44.

    PubMed Central  Google Scholar 

  147. Intipanya P. Relationships between personal factors, lifestyle, and health outcomes in gestational diabetes mellitus women. Bangkok: Faculty of Nursing, Chulalongkorn University; 2005.

    Google Scholar 

  148. Intorn S. Relationships between selected factors and exercise behaviors of middle aged adult in Nakorn Sawan province. Bangkok: Faculty of Nursing, Chulalongkorn University; 2003.

    Google Scholar 

  149. Intusoma U, Mo-Suwan L, Chongsuvivatwong V. Duration and practices of television viewing in Thai infants and toddlers. J Med Assoc Thai. 2013;96(6):650–3.

    PubMed  Google Scholar 

  150. Intusoma U, Mo-suwan L, Ruangdaraganon N, Panyayong B, Chongsuvivatwong V. Effect of television viewing on social-emotional competence of young Thai children. Infant Behav Dev. 2013;36(4):679–85.

    Article  PubMed  Google Scholar 

  151. Isarabhakdi P, Pewnil T. Engagement with family, peers, and Internet use and its effect on mental well-being among high school students in Kanchanaburi Province, Thailand. Int J Adolesc Youth. 2016;21(1):15–26.

    Article  Google Scholar 

  152. Ishimaru T, Arphorn S. Hematocrit levels as cardiovascular risk among taxi drivers in Bangkok, Thailand. Industrial health. 2016;54:433–8.

    Article  PubMed  Google Scholar 

  153. Ivanovitch K, Klaewkla J, Chongsuwat R, Viwatwongkasem C, Kitvorapat W. The intake of energy and selected nutrients by Thai urban sedentary workers: an evaluation of adherence to dietary recommendations. J Nutr Metab. 2014;2014:17.

    Article  CAS  Google Scholar 

  154. Jaarsma T, Strömberg A, Ben Gal T, Cameron J, Driscoll A, Duengen HD, et al. Comparison of self-care behaviors of heart failure patients in 15 countries worldwide. Patient Educ Couns. 2013;92(1):114–20.

    Article  PubMed  Google Scholar 

  155. Jaikhamwang N. Risk behaviors of diabetes and hypertension risk groups: a case study in Ban Pak Ka Yang sub-district, health promoting hospital, Sukhothai province. J Community Dev Life Qual. 2015;3(2):173–84.

    Google Scholar 

  156. Jaitam A. Factors affecting health promoting behaviors of hypertensive patients at Chaturapakpiman hospital, Roi Et province. Khon Kaen: Graduate School, Khon Kaen University; 2002.

    Google Scholar 

  157. Jaiyungyuen U, Suwonnaroop N, Priyatruk P, Moopayak K. Factors influencing health-promoting behaviors of older people with hypertension. 1st Mae Fah Luang University International Conference 2012. Chiang Rai: Mae Fah Luang University; 2012. p. 1–9.

    Google Scholar 

  158. Jalayondeja C, Jalayondeja W, Suttiwong J, Sullivan PE, Nilanthi D. Physical Activity, Self-Esteem, and Quality of Life among People with Physical Disability. Southeast Asian J Trop Med Public Health. 2016;47(3):546–58.

    PubMed  Google Scholar 

  159. Jalayondeja C, Jalayondeja W, Vachalathiti R, Bovonsunthonchai S, Sakulsriprasert P, Kaewkhuntee W, et al. Cross-cultural adaptation of the compendium of physical activity: Thai translation and content validity. J Med Assoc Thai. 2015;98(Suppl 5):S53–S9.

    PubMed  Google Scholar 

  160. Jamjan L, Maliwan V, Pasunant N, Sirapo-ngam Y, Porthiban L. Self-Image of Aging: A Method for Health Promotion. Nurs Health Sci. 2002;4(3):A6.

    Article  Google Scholar 

  161. Janbumrung S. Need for exercising of personnel in Pramongkutklao hospital. Bangkok: Physical Education, Ramkhamhaeng University; 1998.

    Google Scholar 

  162. Jantarapakde J, Phanuphak N, Chaturawit C, Pengnonyang S, Mathajittiphan P, Takamtha P, et al. Prevalence of metabolic syndrome among antiretroviral-naive and antiretroviral-experienced HIV-1 infected Thai adults. AIDS Patient Care STDs. 2014;28(7):331–40.

    Article  PubMed  Google Scholar 

  163. Janyacharoen T, Kunbootsri N, Arayawichanon P, Chainansamit S, Sawanyawisuth K. Responses of Six-Weeks Aquatic Exercise on the Autonomic Nervous System, Peak Nasal Inspiratory Flow and Lung Functions in Young Adults with Allergic Rhinitis. Iran J Allergy, Asthma Immunol. 2015;14(3):280–6.

    Google Scholar 

  164. Janyacharoen T, Laophosri M, Kanpittaya J, Auvichayapat P, Sawanyawisuth K. Physical performance in recently aged adults after 6 weeks traditional Thai dance: A randomized controlled trial. Clin Interv Aging. 2013;8:855–9.

    PubMed  PubMed Central  Google Scholar 

  165. Janyacharoen T, Phusririt C, Angkapattamakul S, Hurst CP, Sawanyawisuth K. Cardiopulmonary effects of traditional Thai dance on menopausal women: A randomized controlled trial. J Phys Ther Sci. 2015;27(8):2569–72.

    Article  PubMed  PubMed Central  Google Scholar 

  166. Janyacharoen T, Sirijariyawat K, Nithiatthawanon T, Pamorn P, Sawanyawisuth K. Modified stepping exercise improves physical performances and quality of life in healthy elderly subjects. J Sports Med Phys Fitness. 2016;57(10):1344–8.

    PubMed  Google Scholar 

  167. Jareonpol O, Paisanpattanasakul Y, Chottidao M. Physical activity and physical fitness level of Mahidol University Employee, s Salaya Campus. Thammasat Med J. 2014;14(4):562–71.

    Google Scholar 

  168. Jarupanich T. Prevalence and risk factors associated with osteoporosis in women attending menopause clinic at Hat Yai Regional Hospital. J Med Assoc Thai. 2007;90(5):865–9.

    PubMed  Google Scholar 

  169. Jaruratanasirikul S, Wongwaitaweewong K, Sangsupawanich P. Electronic game play and school performance of adolescents in Southern Thailand. Cyberpsychol Behav. 2009;12(5):509–12.

    Article  PubMed  Google Scholar 

  170. Jaruwan P, Arpaporn P, Sunee L, Jeeranun K. The diamond level health promoting schools (DLHPS) program for reduced child obesity in Thailand: lessons learned from interviews and focus groups. Asia Pac J Clin Nutr. 2014;23(2):293–300.

    Google Scholar 

  171. Jermsuravong W, Vongjaturapat N, Li F. The influence of exercise motivation on exercise behavior among Thai youth. J Popul Soc Stud. 2008;17(1):93–114.

    Google Scholar 

  172. Jewpattanakul Y, Reungthongdee U, Tabkaew T. The effect of the arm swing exercise with family participation program on exercise behavior in elderly with essential hypertension. J Nurs Sci. 2012;30(2):46–57.

    Google Scholar 

  173. Jiamjarasrangsi W, Attavorrarat S, Navicharern R, Aekplakorn W, Keesukphan P. Assessment of 5-year system-wide type 2 diabetes control measures in a Southeast Asian metropolis. Asian Biomedicine. 2014;8(1):75–82.

    Article  Google Scholar 

  174. Jindawong B, Kuhiranyaratn P, Paileeklee S, Ratanasiri A, See-Ubpalad W. Type, duration, and effect of physical exercise on chronic health diseases among urban elderly in Khon Kaen Province, Thailand. J Aging Phys Act. 2008;16:S57.

    Google Scholar 

  175. Jirapinyo P, Wongarn R, Limsathayourat N, Maneenoy S, Somsa-Ad K, Thinpanom N, et al. Adolescent Height : Relationship to Exercise, Milk Intake and Parents’ Height. J Med Assoc Thai. 1997;80(10):641–6.

    Google Scholar 

  176. Jirasatmathakul P, Poovorawan Y. Prevalence of video games among Thai children: Impact evaluation. J Med Assoc Thai. 2000;83(12):1509–13.

    PubMed  CAS  Google Scholar 

  177. Jirojanakul P, Skevington SM, Hudson J. Predicting young children's quality of life. Soc Sci Med. 2003;57(7):1277–88.

    Article  PubMed  Google Scholar 

  178. Jitapunkul S, Yuktananandana P, Parkpian V. Risk factors of hip fracture among Thai female patients. J Med Assoc Thai. 2001;84(11):1576–81.

    PubMed  CAS  Google Scholar 

  179. Jitnarin N, Kosulwat V, Boonpraderm A, Haddock CK, Poston WS. The relationship between smoking, BMI, physical activity, and dietary intake among Thai adults in central Thailand. J Med Assoc Thai. 2008;91(7):1109–16.

    PubMed  Google Scholar 

  180. Jitramontree N. Predicting exercise behavior among Thai elders: Testing the theory of planned behavior. PhD [dissertation]. Iowa: University of Iowa; 2003.

    Google Scholar 

  181. Jitsacorn C. Perceived benefits and barriers to exercise behavior in coronary artery disease patients. Nakhon Pathom: Faculty of Graduate Studies, Mahidol University; 2000.

    Google Scholar 

  182. Jordan S, Lim L, Berecki-Gisolf J, Bain C, Seubsman SA, Sleigh A, et al. Body mass index, physical activity, and fracture among young adults: longitudinal results from the Thai cohort study. J Epidemiol. 2013;23(6):435–42.

    Article  PubMed  PubMed Central  Google Scholar 

  183. Jordan S, Lim L, Vilainerun D, Banks E, Sripaiboonkij N, S-a S, et al. Breast cancer in the Thai Cohort Study: an exploratory case-control analysis. Breast. 2009;18(5):299–303.

    Article  PubMed  PubMed Central  Google Scholar 

  184. Julvanichpong T. Predictive Factors of Exercise Behaviors of Junior High School Students in Chonburi Province. World Acad Sci, Eng Technol, Int J Soc, Behav, Educ, Econ, Bus Ind Eng. 2015;9(7):2633–8.

    Google Scholar 

  185. Junhasiri N. The effect of an aerobic exercise upon the physical fitness components in elderly women. Bangkok: Srinakharinwirot University; 1993.

    Google Scholar 

  186. Junlapeeya P. Model testing of exercise behavior in Thai female registered nurses in an urban hospital. Baltimore: University of Maryland; 2005.

    Google Scholar 

  187. Kabkaew T. Factors affecting exercise behavior of assistant-nurse students, Hospital for Tropical Disease, Mahidol University. Bangkok: Graduate School, Kasetsart University; 2006.

    Google Scholar 

  188. Kaewanuchit C. A path analysis of mental health among Thai elderly with diabetes mellitus. Pertanika J Sci Technol. 2016;24(2):285–94.

    Google Scholar 

  189. Kaewboonchoo O, Saleekul S, Powwattana A, Kawai T. Blood lead level and blood pressure of bus drivers in Bangkok, Thailand. Ind Health. 2007;45(4):590–4.

    Article  PubMed  CAS  Google Scholar 

  190. Kaewpan W, Kalampakorn S. Health status and health promoting behaviors among aging workers in Thailand. J Med Assoc Thai. 2012;95(SUPPL 6):S16–20.

    PubMed  Google Scholar 

  191. Kaewpan W, Kalampakorn S, Luksamijarulkul P. Factors related to health-promoting behaviors among Thai middle-aged men. J Med Assoc Thai= Chotmaihet thangphaet. 2007;90(9):1916–24.

    PubMed  Google Scholar 

  192. Kaewthong P, Buranruk O, Eungpinitpong W, Soontarapa S. Comparison of Ruesidadton-Chikung combination exercise and Taichi exercise on lower extremities strength and balance in sedentary middle-aged women. J Med Technol Phys Ther. 2015;27(1):79–86.

    Google Scholar 

  193. Kaewthummanukul T, Brown KC, Weaver MT, Thomas RR. Predictors of exercise participation in female hospital nurses. J Adv Nurs. 2006;54(6):663–75.

    Article  PubMed  Google Scholar 

  194. Kaewthummanukul T, Chanprasit C, Poosawang R, Tripibool D, Songkham W. Predictors of exercise among practical nurses. Nurs J. 2008;35(1):22–35.

    Google Scholar 

  195. Kaewwit R. Factors Influencing the Internet Using Behavior of Undergraduate Students in Bangkok and Suburban Areas. BU Acad Rev. 2007;6(1):26–33.

    Google Scholar 

  196. Kallaya K, Thasanasuwan W, Wimonpeerapattana W, Seaburin W, Srichan W, Kunapan P. Relationship of Physical Activity Level, Percent Body Fat, Percent Lean Body Mass and Bone Z-Score in Thai Adolescents. Ann Nutr Metab. 2009;55:717.

    Google Scholar 

  197. Kanchanomai S, Janwantanakul P, Jiamjarasrangsi W. One-year Incidence and Risk Factors of Thoracic Spine Pain in Undergraduate Students. J Phys Ther Sci. 2013;25(1):15–20.

    Article  Google Scholar 

  198. Kanchanomai S, Janwantanakul P, Pensri P, Jiamjarasrangsi W. Prevalence of and factors associated with musculoskeletal symptoms in the spine attributed to computer use in undergraduate students. Work. 2012;43(4):497–506.

    PubMed  Google Scholar 

  199. Kantachuvessiri A, Sirivichayakul C, Kaewkungwal J, Tungtrongchitr R, Lotrakul M. Factors associated with obesity among workers in a metropolitan waterworks authority. Southeast Asian J Trop Med Public Health. 2005;36(4):1057–65.

    PubMed  Google Scholar 

  200. Kanthamalee S, Panuthai S, Chaiwan S. Effects of the self-efficacy and social support enhancement program on exercise behavior and blood pressure among hypertensive elderly. Nurs J. 2007;34(4):93–103.

    Google Scholar 

  201. Karoonngamphan M, Suvaree S, Numfone N. Health Behaviors and Health Status of Workers: A Case Study of Workplaces in Sathorn District, Bangkok Metropolitan. Songklanagarind J Nurs. 2012;32(3):51–66.

    Google Scholar 

  202. Karuncharernpanit S. The effect of an exercise intervention on physical and cognitive function, psychological health and quality of life among older adults with dementia in Bangkok, Thailand. Western Australia: Faculty of Computing, Health and Science, Edith Cowan University; 2012.

    Google Scholar 

  203. Karuncharernpanit S, Hendricks J, Toye C. Perceptions of exercise for older people living with dementia in Bangkok, Thailand: an exploratory qualitative study. Int J Older People Nurs. 2016;11(3):166–75.

    Article  PubMed  Google Scholar 

  204. Keawduangdee P, Puntumetakul R, Swangnetr M, Laohasiriwong W, Settheetham D, Junichiro Y, et al. Prevalence of low back pain and associated factors among farmers during the rice transplanting process. J Phys Ther Sci. 2015;27(7):2239–45.

    Article  PubMed  PubMed Central  Google Scholar 

  205. Keawvilai S. The predictive factors on exercise behaviors of undergraduate students Rajamangala University of Technology Phra Nakhon. Bangkok: Rajamangala University of Technology Phra Nakhon; 2009.

    Google Scholar 

  206. Ketkasan N, Pongpanich S. Examining stages of readiness exercise behavior change among Thai university students. Seoul: KPEAW International Symposium; 2013. p. 175–6.

    Google Scholar 

  207. Kheawwan P, Chaiyawat W, Aungsuroch Y, Bill Wu YW. Patient readiness to exercise after cardiac surgery development of the readiness to change exercise questionnaire. J Cardiovasc Nurs. 2016;31(2):186–93.

    Article  PubMed  Google Scholar 

  208. Kheokao J, Siriwanij W, Yingrengreung S, Krirkgulthorn T, Panidchakult K. Media Use of Nursing Students in Thailand. 2015 4th International Symposium on Emerging Trends and Technologies in Libraries and Information Services (Ettlis); 2015. p. 123–7.

    Google Scholar 

  209. Khongprasert S, Bhidayasiri R, Kanungsukkasem V. A Thai dance exercise regimen for people with Parkinson's disease. J Health Res. 2012;26(3):125–9.

    Google Scholar 

  210. Khongprasert S, Bhidayasiri R, Kanungsukkasem V. Thai Classical Dance: From being part of the culture to being an exercise. Mov Disord. 2014;29:S15–S.

    Article  Google Scholar 

  211. Khotcharrat R, Patikulsila D, Hanutsaha P, Khiaocham U, Ratanapakorn T, Sutheerawatananonda M, et al. Epidemiology of age-related macular degeneration among the elderly population in Thailand. J Med Assoc Thai. 2015;98(8):790–7.

    PubMed  Google Scholar 

  212. Khruakhor S, Sritipsukh P, Siripakar Y, Vachalathit R. Prevalence and risk factors of low back pain among the university staff. J Med Assoc Thai. 2010;93(SUPPL 7):S142–S8.

    Google Scholar 

  213. Khui-apai K. Effect of Tai Chi Qigong exercise on blood pressure and drug use among the elderly with essential hypertension. Chiang Mai: Graduate School, Chiang Mai University; 2005.

    Google Scholar 

  214. Khumprommarach S. Effects of minifitball exercise program on health-related physical fitness and quality of life in working women. Bangkok: Faculty of Sports Science, Chulalongkorn University; 2010.

    Google Scholar 

  215. Khumsri J, Yingyeun R, Manwong M, Hanprathet N, Phanasathit M. Prevalence of facebook addiction and related factors among Thai high school students. J Med Assoc Thai. 2015;98:S51–60.

    PubMed  Google Scholar 

  216. Khunphasee A. Attitude to exercise and cardiopulmonary endurance fitness in staff of rehabilitation department at Phramongkutklao hospital. Royal Thai Army Med J. 2010;63(3):125–34.

    Google Scholar 

  217. Khuntongkaew S. Exercise behavior among health group members at Ratchaburi province. Bangkok: Graduate School, Silpakorn University; 2005.

    Google Scholar 

  218. Khwanchuea R, Thanapop S, Samuhasaneeto S, chartwaingam S, Mukem S. Bone Mass, Body Mass Index, and Lifestyle Factors: A Case Study of Walailak University Staff. Walailak J Sei & Teeh. 2012;9(3):263-75.

  219. Kiatrungrit K, Hongsanguansri S. Cross-sectional study of use of electronic media by secondary school students in Bangkok, Thailand. Shanghai Arch Psychiatry. 2014;26(4):216–26.

    PubMed  PubMed Central  Google Scholar 

  220. Kijboonchoo K, Thasanasuwan W, Seaburin W, Wimonpeerapattana W, Srichan W, Kunapan PI. There Any Gender Difference in Physical Activity Level in Thai Adolescents? Ann Nutr Metab. 2009;55:570.

    Google Scholar 

  221. Kijboonchoo K, Thasanasuwan W, Yamborisut U, Tatsameesopaporn W, Jitjang U, Srichan W. Report of the development of validated body fat, body mass index, and physical activity assessment for Thai children. Bangkok: Institute of Nutrition, Mahidol University; 2007.

    Google Scholar 

  222. Kitrungpipat N, Phannithit A. Self-health care behavior student in Silpakorn University Phrtchaburi IT Campus. Bangkok: Faculty of Management Science, Silpakorn University; 2012.

    Google Scholar 

  223. Kittipimpanon K. Factors Associated with Physical Performance Among Elderly in Urban Poor Community. Nakorn Pathom: Faculty of Graduate Studies, Mahidol University; 2006.

    Google Scholar 

  224. Klainin-Yobas P, He HG, Lau Y. Physical fitness, health behavior and health among nursing students: A descriptive correlational study. Nurse Educ Today. 2015;35(12):1199–205.

    Article  PubMed  Google Scholar 

  225. Klanarong S. Socio-demographic distribution of health-related fitness of Thai children. South Australia: University of South Australia; 2005.

    Google Scholar 

  226. Kongcheewasakul C, Klanarong S, Sathirapanya C. Exercise behavior for health of Rajamangala Srivijaya university students, Songkhla Campus. AL-NUR. 2014;9(16):59–70.

    Google Scholar 

  227. Kongin W. Self-care of the rural Thai elderly. PhD [dissertation]. District of Columbia (DC): Catholic University of America; 1998.

  228. Kongkanand A. Prevalence of erectile dysfunction in Thailand. Thai Erectile Dysfunction Epidemiological Study Group. Int J Androl. 2000;23(Suppl 2):77–80.

    Article  PubMed  Google Scholar 

  229. Konharn K, Karawa J, Maneetam T, Puangsuwan A, Kosolsak M, Nakornkhet K. Validity and reliability of the physical activity questionnaire for Thai children and youth 2015 in age 14–17 year. Bangkok: Physical Activity Research Centre, Thai Health Promotion Foundation; 2016.

  230. Konharn K, Santos MP, Ribeiro JC. Socioeconomic status and objectively measured physical activity in Thai adolescents. J Phys Act Health. 2014;11(4):712–20.

    Article  PubMed  Google Scholar 

  231. Konharn K, Santos MP, Ribeiro JC. Differences between weekday and weekend levels of moderate-to-vigorous physical activity in Thai adolescents. Asia-Pac J Public Health. 2015;27(2):NP2157–NP66.

    Article  PubMed  Google Scholar 

  232. Kornanong Y. Effects of 10,000 steps a day on physical and mental health in overweight participants in a community setting: a preliminary study. Braz J Phys Ther / Revista Brasileira de Fisioterapia. 2016;20(4):367–73.

    Google Scholar 

  233. Kraithaworn P, Sirapo-ngam Y, Piaseu N, Nityasuddhi D, Gretebeck KA. Factors predicting physical activity among older Thais living in low socioeconomic urban communities. Pac Rim Int J Nur Res. 2011;15(1):39–56.

    Google Scholar 

  234. Krittatunmakul S. Guidelines for transport system improvement for promoting physical activities of Trang city. Bangkok: Faculty of Architecture, Chulalongkorn University; 2013.

    Google Scholar 

  235. Kruavit A, Chailurkit LO, Thakkinstian A, Sriphrapradang C, Rajatanavin R. Prevalence of Vitamin D insufficiency and low bone mineral density in elderly Thai nursing home residents. BMC Geriatrics. 2012;12(1):49.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  236. Kuhiranyaratn P, Jindawong B, Paileeklee S, Ratanasiri A, See-Ubpalad W. Social support and physical exercise among rural elderly in Khon Kaen province, Thailand. J Aging Phys Act. 2008;16:S186–S.

    Google Scholar 

  237. Kuhirunyaratn P, Prasomrak P, Jindawong B. Factors related to falls among community dwelling elderly. Southeast Asian J Trop Med Public Health. 2013;44(5):906–15.

    PubMed  Google Scholar 

  238. Kumkate B, Wongpat P, Sanjaroensuttikul N. Effect of Tai Chi Chun exercise on balance in Thai elderly people. J Thai Rehabil Med. 2007;17(3):73–8.

    Google Scholar 

  239. Kuptniratsaikul V, Tosayanonda O, Nilganuwong S, Thamalikitkul V. The Efficacy of a Muscle Exercise Program to Improve Functional Performance of the Knee in Patients with Osteoarthritis. J Med Assoc Thai. 2002;85(1):33–40.

    PubMed  Google Scholar 

  240. Kuramasuwan B, Howteerakul N, Suwannapong N, Rawdaree P. Diabetes, impaired fasting glucose, daily life activities, food and beverage consumption among Buddhist monks in Chanthaburi Province, Thailand. Int J Diabetes Dev Countries. 2013;33(1):23–8.

    Article  CAS  Google Scholar 

  241. Kurmlue P. Factors affecting Payap university students. Chiang Mai: Graduate School, Chiang Mai University; 2000.

    Google Scholar 

  242. L-Y, Lim L, Kjellstrom T, Sleigh A, Khamman S, Seubsman S-A, Dixon J, et al. Associations between urbanisation and components of the health-risk transition in Thailand. A descriptive study of 87,000 Thai adults. Global Health Action. 2009;2(1):1914.

  243. Lam LCW, Ong PA, Dikot Y, Sofiatin Y, Wang H, Zhao M, et al. Intellectual and physical activities, but not social activities, are associated with better global cognition: A multi-site evaluation of the cognition and lifestyle activity study for seniors in Asia (CLASSA). Age Ageing. 2015;44(5):835–40.

    Article  PubMed  Google Scholar 

  244. Laophosri M, Kanpittaya J, Sawanyawisuth K, Auvichayapat P, Janyacharoen T. Effects of Thai dance on balance in Thai elderly. Chula Med J. 2013;57(3):345–57.

    Google Scholar 

  245. Laosupap K, Sota C, Laopaiboon M. Factors affecting physical activity of rural Thai midlife women. J Med Assoc Thai. 2008;91(8):1269–75.

    PubMed  Google Scholar 

  246. Lau EM, Suriwongpaisal P, Lee JK, Das De S, Festin MR, Saw SM, et al. Risk factors for hip fracture in Asian men and women: the Asian osteoporosis study. J Bone Miner Res. 2001;16(3):572–80.

    Article  PubMed  CAS  Google Scholar 

  247. Lavichant A. Factors affecting the internet usage behavior of undergraduate and graduate students in Bangkok metropolitan area. Bangkok: Graduate School, Srinakharinwirot University; 2006.

    Google Scholar 

  248. Lazzarino AI, Yiengprugsawan V, Sam-ang S, Steptoe A, Sleigh AC. The associations between unhealthy behaviours, mental stress, and low socio-economic status in an international comparison of representative samples from Thailand and England. Glob Health. 2014;10(1):1–18.

    Article  Google Scholar 

  249. Le D, Garcia A, Lohsoonthorn V, Williams MA. Prevalence and risk factors of hypercholesterolemia among Thai men and women receiving health examinations. Southeast Asian J Trop Med Public Health. 2006;37(5):1005–14.

    PubMed  Google Scholar 

  250. Leelacharas S, Kerdonfag P, Chontichachalalauk J, Sanongdej W. Illness Perceptions, Lifestyle Behaviors, Social Support, and Cardiovascular Risks in People with Hypertension in Urban and Rural Areas of Thailand. Pac Rim Int J Nurs Res. 2015;19(3):245–56.

    Google Scholar 

  251. Leelarungrayub D, Pratanaphon S, Pothongsunun P, Sriboonreung T, Yankai A, Bloomer RJ. Vernonia cinerea less supplementation and strenuous exercise reduce smoking rate: relation to oxidative stress status and beta-endorphin release in active smokers. J Int Soc Sports Nutr. 2010;7:21–30.

    Article  PubMed  PubMed Central  Google Scholar 

  252. Leelarungrayub D, Saidee K, Pothongsunun P, Pratanaphon S, YanKai A, Bloomer RJ. Six weeks of aerobic dance exercise improves blood oxidative stress status and increases interleukin-2 in previously sedentary women. J Bodyw Mov Ther. 2011;15(3):355–62.

    Article  PubMed  Google Scholar 

  253. Leelayuwat N, Tunkumnerdthai O, Donsom M, Punyaek N, Manimanakorn A, Kukongviriyapan U, et al. An alternative exercise and its beneficial effects on glycaemic control and oxidative stress in subjects with type 2 diabetes. Diabetes Res Clin Pract. 2008;82(2):e5–8.

    Article  PubMed  Google Scholar 

  254. Leemingsawat W, Chakraphan D, Benjapalakorn B, Kamawatana U, Siripatt A. A study of exercise behaviors of students in higher education institutes. J Sports Sci Health. 2007;8(1):24–37.

    Google Scholar 

  255. Leethong-in M. A causal model of physical activity in healthy older Thai people. Bangkok: Faculty of Nursing, Chulalongkorn University; 2009.

    Google Scholar 

  256. Leethong-in M, Yunibhand J, Aungsuroch Y, Magiivy JK, Leethong-in M, Yunibhand J, et al. Assessment of the environmental support for physical activity scale among Thai elderly. Chula Med J. 2011;55(5):421–35.

    Google Scholar 

  257. Leggat PA, Chowanadisai S, Kedjarune U, Kukiattrakoon B, Yapong B. Health of dentists in southern Thailand. Int Dental J. 2001;51(5):348–52.

    Article  CAS  Google Scholar 

  258. Lerssrimongkol C, Wisetborisut A, Angkurawaranon C, Jiraporncharoen W, Lam KB. Active commuting and cardiovascular risk among health care workers. Occup Med (Oxford, England). 2016;66(6):483–7.

    Article  CAS  Google Scholar 

  259. Liangchawengwong S, Pothiban L, Panuthai S, Boonchuang P. Prevalence, Stages of Change for Lifestyle-Related Cardiovascular Risk Factors, and Influencing Factors of Physical Activity among Thai Young Adults. Pac Rim Int J Nurs Res. 2013;17(3):217–33.

    Google Scholar 

  260. Limachan R. Physical activity and health status of professional nurses at Bangkok Metropolitan Administration Medical College and Vajira hospital. Bangkok: Graduate School, Srinakharinwirot University; 2006.

    Google Scholar 

  261. Limpaphayom K, Bunyavejchevin S, Panyakhamlerd K, Poshyachinda M, Taechakraichana N. Risk factors of osteoporosis in Thai postmenopausal women attending menopause clinic at Chulalongkorn Hospital. 1st Asian-European Congress on the Menopause; 1998. p. 181–5.

    Google Scholar 

  262. Limpawattana P, Assantachai P, Krairit O, Kengkijkosol T, Wittayakom W, Pimporm J, et al. The predictors of skeletal muscle mass among young Thai adults: A study in the rural area of Thailand. Biomed Res (India). 2016;27(1):29–33.

    CAS  Google Scholar 

  263. Lindholm A, Baylis R. Food consumption, physical activity and sedentary activities among 12-13 year old school children in a rural and an urban area of Thailand. Uppsala: Uppsala University; 2009.

    Google Scholar 

  264. Loipha S. Thai Elderly Behavior of Internet Use. 3rd International Conference on Integrated Information. Procedia Soc Behav Sci. 2014;147:104–10.

    Article  Google Scholar 

  265. Lundberg PC, Thrakul S. Diabetes type 2 self-management among Thai Muslim women. J Nurs Healthc Chronic Illn. 2011;3(1):52–60.

    Article  Google Scholar 

  266. Mahanonda N, Bhuripanyo K, Leowattana W, Kangkagate C, Chotinaiwattarakul C, Panyarachun S, et al. Regular exercise and cardiovascular risk factors. J Med Assoc Thai. 2000;83(Suppl 2):S153–S8.

    PubMed  Google Scholar 

  267. Mai-um W, Hiransuthikul N, Sritara P, Tunlayadechanont S, Larbcharoensub N, Wongwichai S, et al. Stroke incidences and related factors among employees working at the central office of the electricity generating authority of Thailand (EGAT): a prospective-descriptive study. J Health Res. 2014;28(1):13–21.

    Google Scholar 

  268. Makesrithongkum B, Internet use of Thai children and youth at various stages of age development. Proceedings of the IADIS International Conference WWW/Internet 2009, ICWI 2009; 2009.

    Google Scholar 

  269. Mamom J. AOS8 Effectiveness of an education-combining exercise programme for chemotherapy-related fatigue in women with breast cancer. Eur J Cancer. 2012;48(s4):S6–S.

    Article  Google Scholar 

  270. Mandal GK. Physical activity, dietary habits and blood pressure of hypertensive patients in Phutthamonthon district, Nakorn Pathom province, Thailand. Nakorn Pathom: Faculty of Graduate Studies, Mahidol University; 2009.

    Google Scholar 

  271. Maneedang P. The Effectiveness of Dietary and Exercise Behavior Development Program for Overweight Students. Nakhon Pathom: Faculty of Graduate Studies, Mahidol University; 2007.

    Google Scholar 

  272. Mateeskunkan S. A Motivational Study of Exerciser in Bangkok Metropolitan Administration Public Parks. Nakhon Pathom: Faculty of Graduate Studies, Mahidol University; 2003.

    Google Scholar 

  273. McCaffrey R, Ruknui P, Hatthakit U, Kasetsomboon P. The effects of yoga on hypertensive persons in Thailand. Holist Nurs Pract. 2005;19(4):173–80.

    Article  PubMed  Google Scholar 

  274. Merakate J. Leisure participation of youths aged between 12-18 at Suk Samran district, Ranong Province. Kasetsart J - Soc Sci. 2007;28(2):202–9.

    Google Scholar 

  275. Methapatara W, Srisurapanont M. Pedometer walking plus motivational interviewing program for Thai schizophrenic patients with obesity or overweight: A 12-week, randomized, controlled trial. Psychiatry Clin Neurosc. 2011;65(4):374–80.

    Article  Google Scholar 

  276. Mhaopech K, Choupanich K, Lapho P, Teamtaokerd W. Behaviors for exercises of personnel in Kasetsart University, Kampheangsaen Campus. Bangkok: Kasetsart University, and Thai Health Promotion Foundation; 2012.

    Google Scholar 

  277. Mizumoto K. Hypertension and risk factors related to lifestyle among women aged 40 years and over in Phuthamontthon district, Nakhon Pathom province, Thailand. Nakhon Pathom: Faculty of Graduate Studies, Mahidol University; 2004.

    Google Scholar 

  278. Mo-suwan L, Junjana C, Puetpaiboon A. Increasing obesity in school children in a transitional society and the effect of the weight control program. Southeast Asian J Trop Med Public Health. 1993;24(3):590–4.

    PubMed  CAS  Google Scholar 

  279. Mo-suwan L, Nontarak J, Aekplakorn W, Satheannoppakao W. Computer Game Use and Television Viewing Increased Risk for Overweight among Low Activity Girls: Fourth Thai National Health Examination Survey 2008–2009. Int J Paediatr. 2014;2014:1–6.

    Article