Development and validation of a tool to assess the physical and social environment associated with physical activity among adults in Sri Lanka

The burden of mortality, morbidity and disability due to non-communicable diseases (NCDs) is high and is increasing in the developing countries [1]. Physical inactivity is identified as the fourth leading risk factor for mortality due to NCDs and contributes to 6% of deaths globally [2]. In 2001, 71% of all deaths in Sri Lanka were due to chronic NCDs and chronic NCD mortality is reported to be 20-30% higher in Sri Lanka than in many developed countries [3]. According to the Annual Health Statistics, coronary heart disease was the leading cause of hospital deaths in Sri Lanka since 1997 [4]. The World Health Survey data collected in 2002–2003 revealed that in Sri Lanka 7.3% of the males and 13.8% of the females were physically inactive [5].

Being physically active is influenced by both the physical and social environment [6, 7] and is best explained through a socio-ecological model of health related behaviours. Many studies have recognized that environmental factors have a significant role in promoting PA among adults [8‐13] and changing behaviours in an entire community [14]. Literature identifies some common physical (built) environment factors associated with PA. They are land-use patterns, transport systems, urban design, green space, availability of pavements, heavy traffic, street lights, unattended dogs, enjoyable scenery, high levels of crime, and easy access to recreation and retail shops [15, 16]. Income, equity, culture and social support are identified in literature as elements in the social environment that influences participation in PA [17, 18].

Considering the apparent importance of the environment for PA, there is limited information in the literature on how best to measure various aspects of the environment. Evidence on the associations between the physical environment and PA behaviour is derived mostly from self-reported data on individuals’ perceptions of their environments [19]. Observational methods is another form where individuals using checklists, rates the environment. The introduction of geographic information systems into PA research has revolutionised the measurement of the physical environment, and is still in its early stages [20]. Two major types of PA that have been studied in relation to the environment are the recreational PA and PA through non motorized transportation- walking/cycling. An accepted method of measuring the perceived physical environment is through population based studies and surveillance systems [21]. Individual responses can then be aggregated to identify patterns in environment characteristics. Thereafter, it is possible to determine the association between the design characteristics of the environment and behaviour [22]. There are different tools developed for assessment of environment characteristics that are related to different types of PA.

Abbreviated Neighbourhood Environment Walkability Scale (ANEWS) and the International Physical Activity Questionnaire- environmental (IPAQ-e) are two tools that have been extensively used. ANEWS, a 98 question, self-administered instrument to determine the perception of neighbourhood design features hypothesised to be related to PA [23] was developed in San Diego. It consists of six subscales of land use mix-access, street connectivity, infrastructure for walking/cycling, aesthetics, traffic safety and crime safety [24]. IPAQ-e is a 17 item, 4 factor tool which is considered to be relevant to all countries regardless of the stage of economic development [25], with the factors being the degree of urbanisation, traffic intensity, aesthetics and opportunity and fear of crime [26]. There are several other tools which have been developed in America, Europe and Australia to measure the environment associated with PA. All the above mentioned instruments are known to have an average interviewer administration time of 24–30 minutes [23]. Although tools to assess physical and social environment associated with PA in adults have been developed, validated and utilized extensively in developed countries, South Asia and particularly Sri Lanka lacks a validated tool to assess physical and social environment associated with PA. The purpose of conducting this study was to develop and pilot a tool to assess the physical and social environment associated with PA among adults in the district of Colombo and to assess the construct validity and reliability of it.

An active lifestyle is a complex behavioural process that is influenced by various factors of which environmental factors are well recognized [19, 34, 35]. This study was designed to develop a valid and reliable tool to assess the physical and social environment associated with PA in the Colombo district, considering the socio-ecological model for PA behaviour.

The procedure adopted to develop PASES was similar to the procedures used for the development of many other study instruments to assess the physical and social environment for PA in other countries [36, 37]. The steps included: defining the construct, item generation, analysis of the content of items and item reduction, field testing and validation of the developed instrument [38, 39]. Both the quantitative and qualitative research methods provided comprehensive methodologies for exploration of ideas [38], including key informant interviews and in-depth interviews [28]. Item reduction initially was through a simple and non statistical method where a group of experts rated the importance of each item for the appropriateness of the item to the main construct independently. This method facilitated uninfluenced views of each expert as they did not meet each other [40]. According to guidelines of developing new instruments [38], PCA was carried out on a data set that was gathered by administering the translated items to a group of people considered to be similar to the population that the developed instrument was intended to be used [41]. PCA explored the factor structure of the scale and showed that all the items loaded well (factor loadings >0.4) to 8 factors. Hence, no further reduction of data was required through PCA.

CFA on the multi-dimensional construct showed adequate model fit despite emergence of 8 latent factors for the 34 items. Although the PASES was a 8 factor model, the ANEWS had a 6 factor structure after CFA [42] and the IPAQ-e module had 4 factors after PCA [26]. This was expected as some of the items in the three instruments differed. The PASES had two social factors while the ANEWS and IPAQ-e had no social factors.

In the reliability assessment, the Chronbach’s Alpha for physical environment sub-division was 0.487 and for the social environment subdivision was 0.823, indicating a moderate reliability. However, the reliability findings of the present study are comparable with most of reliability tests carried out on environment assessment tools [43, 44]. The test re-test reliability in the present study was between 0.6-0.9, confirming the ability of the PASES to generate reproducible results.

The factors identified and validated were comparable with other tools developed in the USA and Europe, with some variation. Infrastructure for walking has been a common factor identified in many instruments [23] and have shown to be associated with the total PA and walking both for leisure and transport [13, 45]. Items relating to access and connectivity and the infrastructure for walking were seen to load together as ‘degree of urbanisation’ [26] in the IPAQ-e module but the PASES identified it separately as in the ANEWS [24]. Aesthetics and facilities for cycling were identified as one factor in the PASES as the perception of the beauty of the environment and facilities for cycling were perceived in a similar manner in the Sri Lankan setting. However aesthetics were a separate factor in both the ANEWS and IPAQ-e tools. Vehicular traffic safety, and safety which are important factors in the environment, were identified in the newly developed and validated tool, with additional factor of ‘recreational facilities for PA’. Two social factors, namely social cohesion and social acceptance of PA were identified as important and were incorporated to the PASES. Although not factor analysed ‘residential density’ and ‘land use mix diversity’ were components of the newly developed tool PASES. These two components measure proximity, indicating how close different travel destinations are to one another in space. Density indicates the concentration of people, dwelling units or households [45] and mixture of use of land refers to the spatial placement of different types of land uses (industrial, residential, commercial). The factors identified in the PASES were in some ways similar to other environmental assessment tools with some variation which might reflect the Asian setting.

However, it should be noted that findings of factor analysis assessments are often sample specific [46] and generalizability of these findings to other populations would depend on their similarity to this study population. The specific “aspects” that could be studied may vary from within and between countries. This study instrument could be used to assess the physical and environmental factors associated with PA in South Asia and other parts of Sri Lanka after testing for reliability and validity in that particular setting.

A valid and reliable tool to assess the physical and social environment associated with PA was developed in Sri Lanka. This work contributes to a set of tools which can be used by researchers to identify the current perception of the environment for participation in PA by the community and to assess any change in the perception with interventions and with time.

SDW is a lecturer in the Department of Community Medicine, University of Colombo. DF is the Emeritus Professor of Community Medicine, University of Colombo and JF is a senior lecturer in the Department of Geology, University of Peradeniya and is the coordinator, Msc programme in GIS and Remote Sensing at the University of Peradeniya Sri Lanka.