Introduction:
Many countries have ageing populations. In Thailand, people aged 60 years and over comprise 19% of the total population and it is estimated to reach 36% by 2050 (1). The life expectancy of those in this age group had also been continuously increasingly for decades. In the period of 1980-1985, people at the age of 60 years had an average life expectancy of 18 years and it is estimated to be about 23 years by 2020-2025 and subsequently, around 28 years by 2070-2075 (1). Living longer lives though may also denote that the older people are exposed to the risk of living their lives in disability (2,3).
It is important that people in their advanced ages have socially integrated lifestyle with a level of independence (4). Physical limitations resulting to mobility issues are common among older adults whereby comorbidities of the former including obesity and arthritis are also prevalent among those in the said age group (5). Impediments to physical activity have an effect on the other health dimensions, namely psychological state and cognitive performance, and the perceived quality of life of older people (6,7). There are several studies among the older adults of Thailand involving physical limitations which were often measured through activities of daily living (ADL) and instrumental activities of daily living (IADL). In those studies, physical limitation is considered the dependent variable for a list of covariates (8,9); or either ADL or IADL were utilised as independent indices to describe or predict other health-related outcomes such as care needs (10,11) and healthy life expectancies (3,12,13). Such approaches to studying physical limitations are valuable but functional statuses can be viewed as more nuanced and all forms can be analysed concurrently.
This study’s aim was to distinguish among the older population who has a specific degree of functional status given their respective physical limitations. This is done by considering functional status through a scale rather than as a dichotomy (14). Through this approach, individuals in the sample were categorised exclusively into those who are functionally independent, with functional limitation, ADL, or IADL.
This study further examined the prevalence of physical limitations among older persons in the five regions of Thailand: North, Northeast, South, Central, and Bangkok. Universal health insurance has been implemented in the country in 2002 but, geographical and socioeconomic disparities remain with regard to healthcare behaviour and service utilisation (15–17). People in the same regions and in rural areas have apprehensions surrounding primary care settings because of their low service quality and long wait durations (18). These issues stem from the lower density of health care personnel in poorer regions as in the case of the North and the Northeast (19). Visiting private health facilities or even higher-level public hospitals is accessible to those in the urban areas or those with higher socioeconomic capacities in general (16,19).
Material and Method
Data source
This study used the nationally-representative, cross-sectional survey of Population Change and Well-being in the Context of Ageing Societies (PCWAS). This survey was collected in 2016 by the College of Population Studies, Chulalongkorn University in order to gather information about the fertility and ageing situation of Thailand (20). Women in their reproductive ages (15-49 years old) and older adults (60 years old and over) were categories for the target population. From the multistage sampling approach with geographical and administrative stratifications, the resulting sample consisted of 16,912 persons from 15,225 households in 21 provinces within the five regions of the country.
The initial sample of older persons was 7,451. Restrictions to the sample were implemented because self-reported health measures were utilised in the analyses. Firstly, those within the sample who had proxies answering in behalf of the older person for any part of the survey were restricted. This criterion trimmed the sample to 6,525 persons. After which, only those with complete, valid responses to all variables in the current analysis were retained. The final analytical sample was 6,466 respondents. To test for the generalisability of the findings given the restrictions to the sample, a comparison of the complete and the analytical samples was performed and no statistical significance was found between the prevalence of physical limitations and selected individual characteristics such as age, marital status, educational attainment, and income level.
Measures
Physical function status
The categories for physical function status was adopted from the scale utilised by Porell and Miltiades (14) which ranged from being functionally independent, having functional limitations, IADL limitation; and finally, ADL limitations. These discrete categories reflect the degree of physical limitations whereby the category of ADL takes precedence over the classification of IADL; from which the subsequent category was having functional limitations. ADL is the capacity of an older individual to perform, without assistance, the following tasks: eating, getting dressed, bathing, washing the face and teeth, toileting, combing and shaving, and putting on shoes. IADL involved the capacity to take the bus, count money correctly, and take medication. Functional limitations pertain to the inability to independently perform the following tasks: squatting, lifting heavy objects weighing about 5 kg., walking 200-300 metres, and walking up 2-3 steps on the stairs.
An individual is categorised in ADL if a limitation within the respective abovementioned list was reported. A categorisation of IADL is for those who have such limitations but no limitation in the ADL category. Being classified into having functional limitation was for those with such corresponding physical limits but have no ADL nor IADL limitations. An individual was classified as independent when no physical limitation was reported.
Regions
Thailand has five regions: North, Northeast, South, Central, and Bangkok. Bangkok is the capital city of the country. It is geographically located in the Central region but, as it has much differences in terms of socioeconomic status, infrastructure, and lifestyle, it warrants its own category as in previous studies (12,21).
Sociodemographic characteristics
Information collected from respondents included age, gender, marital status (Married, widowed, separated/divorced/never married), living arrangement (living with others, living alone), education attainment (≤Compulsory level [4th grade], >compulsory level), average annual income (<50,000 Baht, ≥50,000 Baht), perceived adequacy of income, employment status, and social activity participation.
Health behaviour and condition
Health risks information including smoking tobacco and drinking alcohol were gathered by asking the respondents “In the past six months, have you consumed the following?”; to which they were able to respond with no, sometimes, and every day. The latter two options were combined to denote the intake of alcohol or tobacco. A dichotomous index was created to represent proper health behaviours; and it represents doing the following regularly: drinking eight glasses of water, eating fruits and vegetables every day, and exercising daily. Information was also gathered about visiting a physical annually for a general diagnostic check regardless of being in a private or public facility.
Self-rated health had five response categories: very poor, poor, fair, good, and very good. It was considered self-rated poor health in this study by combining very poor to fair categories. Vision and auditory impairment was the inability to see or hear regardless of having an assistive device or otherwise. Incontinence involved the experience of uncontrolled bowel or urinary extraction in the past month from the survey date.
The PCWAS offered no clinical diagnostic information about the respondent therefore the psychological and cognitive health dimension variables in this study represent the presence of symptoms and the level of performance respectively (22). Depression symptoms is measured by having at least one of the following feelings in the previous month from the survey: having no hope in life, worthlessness, unhappiness, and loneliness. Cognitive performance was assessed through the performance of memory and numeracy tasks. The memory test involved memorising a list of words and reciting it back to the enumerator while numeracy tasks involved the mental calculation of serial subtraction. The total score for cognition was eight (8) and if the respondent scored half or less than that, it would be categorised as having ‘poor cognitive performance’.
Statistical analysis
As mentioned above, functional status was measured in a scale to distinguish between each older person’s experience of physical limitation (14). The multinomial logit regression model was appropriate because of the nature of the said measure with the reference category being those who are functionally independent.
A multi-model approach was applied for the current analysis to observe the correlation of regional residence vis-à-vis the covariates with each category of functional status. In Model 1, only the regions of residence were included. In Model 2, the sociodemographic variables were incorporated to determine the effect of demographic characteristics and also socioeconomic factors including education and income. Lastly, Model 3 included health behaviours and conditions. In order to show the effect of the set of variables included for each model, the Wald statistic was observed while the McFadden R2 was used to estimate model fit. Sampling weights were used for the analyses.
Results
The sample distribution according to functional statuses are shown in Table 1. Based on the region of residence, most people in the Northeast were functionally independent at 58%. The least number of people free of physical limitations were in Bangkok. For the sociodemographic factors, increasing age was observed to be proportional to increasing physical limitations particularly on IADLs. The other characteristics that were observed to have higher prevalence of functional independence were being male, married people, having higher education attainment and income level, having perceived adequate income, being employed, and participating in social activities.
| Table 1: Characteristics of older persons in Thailand by functional status |
|
Total |
Functionally independent |
Functional limitations |
IADL limitations |
ADL limitations |
Regions |
|
|
|
|
|
Bangkok |
588 |
40.7 |
33.4 |
21.2 |
4.8 |
Central (exc. Bangkok) |
1675 |
49.1 |
22.8 |
23.5 |
4.5 |
North |
1345 |
44.2 |
26.8 |
23.6 |
5.4 |
Northeast |
2153 |
58.0 |
13.3 |
25.8 |
2.9 |
South |
705 |
45.3 |
22.4 |
29.4 |
2.8 |
Sociodemographic factors |
|
|
|
|
|
Age |
|
|
|
|
|
60–69 |
3905 |
59.6 |
22.4 |
15.8 |
2.3 |
70-79 |
1985 |
39.6 |
20.0 |
35.1 |
5.2 |
80 and over |
575 |
19.6 |
19.4 |
49.6 |
11.3 |
Female |
3653 |
38.1 |
24.4 |
32.6 |
4.8 |
Marital status |
|
|
|
|
|
Married |
4280 |
56.2 |
20.8 |
19.6 |
3.4 |
Widowed |
1688 |
36.2 |
21.8 |
36.6 |
5.5 |
Separated/ divorced/ never married |
498 |
42.3 |
25.2 |
28.7 |
3.8 |
Living alone |
672 |
42.5 |
21.0 |
32.3 |
4.2 |
Education attainment |
|
|
|
|
|
Compulsory education and lower |
5315 |
47.4 |
20.6 |
27.7 |
4.3 |
Higher than compulsory level |
1151 |
61.5 |
24.9 |
10.9 |
2.7 |
Higher income level (≥30,000 Baht/month) |
2586 |
57.7 |
24.3 |
16.1 |
1.9 |
Adequate income |
3459 |
53.5 |
20.9 |
22.7 |
2.9 |
Employed in the past year |
3291 |
63.3 |
20.2 |
14.8 |
1.7 |
Participated in social activities |
3375 |
52.8 |
22.5 |
22.1 |
2.6 |
Health behaviours and condition |
|
|
|
|
|
Smoking tobacco |
1093 |
70.1 |
14.3 |
13.1 |
2.5 |
Drinking alcohol |
1190 |
70.5 |
16.6 |
11.4 |
1.4 |
Proper health behaviour |
2724 |
62.0 |
17.9 |
18.6 |
1.5 |
Has annual health check |
1649 |
50.0 |
26.0 |
20.7 |
3.3 |
Self-rated poor health |
1578 |
26.8 |
27.9 |
36.3 |
9.0 |
Visually impaired |
3162 |
42.8 |
22.5 |
29.4 |
5.4 |
Hearing impaired |
763 |
34.4 |
21.0 |
37.7 |
6.9 |
Experience of incontinence |
1513 |
33.1 |
24.1 |
35.4 |
7.5 |
Experienced 1+ depressive symptom |
2580 |
36.4 |
24.6 |
31.9 |
7.0 |
Poor cognitive performance |
828 |
33.1 |
15.7 |
45.1 |
6.1 |
Number of observations |
6466 |
49.9 |
21.4 |
24.7 |
4.0 |
Source: 2016 PCWAS |
In Table 2, the multinomial logit model of functional status is presented. It was observed that functional limitations were more prevalent among older persons in Bangkok compared with the four regions of the country. This was evident across the three models where all sociodemographic and health-related covariates were included in the analysis. In Model 3 in particular, the relative risk ratios for Northeast, Central, South, and North were about 0.3, 0.6, 0.7, and 0.8 respectively. The occurrence of having IADL was significantly different only for Central and Northeast regions. This denotes that IADL was associated with Bangkok rather than the two mentioned regions. ADL on the other hand, was also associated with Bangkok when compared with Central, Northeast, and South regions.
| Table 2: Association of physical activity with sociodemographic characteristics, health behaviours, and health perception and condition |
|
Functional limitation |
Variable (Reference) |
Model 1 |
Model 2 |
Model 3 |
RRR |
95% CI |
RRR |
95% CI |
RRR |
95% CI |
Region (Bangkok) |
|
|
|
|
|
|
Central [exc. Bangkok] |
0.57*** |
[0.44, 0.72] |
0.59*** |
[0.45, 0.76] |
0.56*** |
[0.43, 0.74] |
North |
0.74** |
[0.57, 0.95] |
0.77* |
[0.57, 1.03] |
0.83* |
[0.61, 1.13] |
Northeast |
0.28*** |
[0.22, 0.36] |
0.29*** |
[0.21, 0.39] |
0.30*** |
[0.22, 0.40] |
South |
0.60*** |
[0.46, 0.78] |
0.64** |
[0.48, 0.85] |
0.67** |
[0.50, 0.91] |
Sociodemographic factors |
Age |
|
|
1.04*** |
[1.02, 1.05] |
1.03*** |
[1.02, 1.05] |
Female (Male) |
|
|
1.95*** |
[1.57, 2.41] |
1.87*** |
[1.50, 2.32] |
Urban residence (Rural) |
|
|
0.57** |
[0.36, 0.91] |
0.58** |
[0.35, 0.92] |
Marital status (Married) |
|
|
|
|
|
|
Widowed |
|
|
0.95 |
[0.75, 1.20] |
0.94 |
[0.74, 1.19] |
Separated/divorced/never married |
|
|
0.97 |
[0.70, 1.34] |
0.98 |
[0.70, 1.38] |
Living alone (Living with others) |
|
|
0.95 |
[0.69, 1.31] |
0.87 |
[0.62, 1.20] |
Higher than compulsory level (Compulsory level and below) |
|
|
0.85** |
[0.67, 1.07] |
0.94** |
[0.74, 1.19] |
Higher average annual income level (Lower income level) |
|
|
0.63* |
[0.45, 0.92] |
0.62* |
[0.43, 0.90] |
Income adequacy (Inadequate) |
|
|
0.75** |
[0.62, 0.91] |
0.90* |
[0.74, 1.10] |
Employed in the past year (Not employed) |
|
|
0.65*** |
[0.53, 0.79] |
0.67*** |
[0.55, 0.83] |
Participated in community activities (No participation) |
|
|
0.93* |
[0.72, 1.18] |
0.97* |
[0.76, 1.22] |
Health behaviours and condition |
Smoke tobacco (No) |
|
|
|
|
0.68 |
[0.51, 0.92] |
Drink alcohol (No) |
|
|
|
|
0.80 |
[0.61, 1.05] |
Proper health behaviour (No) |
|
|
|
|
0.79 |
[0.65, 0.96] |
Has annual health check (No) |
|
|
|
|
1.16 |
[0.94, 1.42] |
Self-rated poor health (Good) |
|
|
|
|
2.37*** |
[1.88, 2.99] |
Vision impairment (No) |
|
|
|
|
1.13* |
[0.93, 1.37] |
Hearing impairment (No) |
|
|
|
|
1.33* |
[0.96, 1.84] |
Experience incontinence (No) |
|
|
|
|
1.45** |
[1.15, 1.82] |
Experienced 1+ depressive symptom (No) |
|
|
|
|
1.59*** |
[1.31, 1.95] |
Poor cognitive performance (Good cognitive performance) |
|
|
|
|
0.94 |
[0.66, 1.32] |
|
IADL |
Variable (Reference) |
Model 1 |
Model 2 |
Model 3 |
RRR |
95% CI |
RRR |
95% CI |
RRR |
95% CI |
Region (Bangkok) |
|
|
|
|
|
|
Central [exc. Bangkok] |
0.92* |
[0.71, 1.19] |
0.69** |
[0.51, 0.92] |
0.67** |
[0.49, 0.91] |
North |
1.03 |
[0.78, 1.34] |
0.93 |
[0.66, 1.31] |
1.05 |
[0.74, 1.49] |
Northeast |
0.86* |
[0.67, 1.09] |
0.61** |
[0.45, 0.82] |
0.62** |
[0.45, 0.85] |
South |
1.25 |
[0.96, 1.61] |
0.93 |
[0.69, 1.25] |
1.01 |
[0.74, 1.37] |
Sociodemographic factors |
Age |
|
|
1.11*** |
[1.09, 1.12] |
1.10*** |
[1.08, 1.11] |
Female (Male) |
|
|
2.89*** |
[2.26, 3.68] |
2.73*** |
[2.12, 3.51] |
Urban residence (Rural) |
|
|
0.91* |
[0.75, 1.10] |
0.92* |
[0.75, 1.20] |
Marital status (Married) |
|
|
|
|
|
|
Widowed |
|
|
0.92 |
[0.72, 1.17] |
0.90 |
[0.70, 1.16] |
Separated/divorced/never married |
|
|
1.04 |
[0.72, 1.52] |
1.05 |
[0.69, 1.58] |
Living alone (Living with others) |
|
|
1.10 |
[0.80, 1.51] |
0.97 |
[0.69, 1.35] |
Higher than compulsory level (Compulsory level and below) |
|
|
0.43*** |
[0.33, 0.58] |
0.50*** |
[0.38, 0.67] |
Higher average annual income level (Lower income level) |
|
|
0.80* |
[0.64, 1.00] |
0.80* |
[0.64, 1.01] |
Income adequacy (Inadequate) |
|
|
0.65*** |
[0.53, 0.80] |
0.81* |
[0.65, 1.00] |
Employed in the past year (Not employed) |
|
|
0.51*** |
[0.41, 0.63] |
0.53*** |
[0.42, 0.66] |
Participated in community activities (No participation) |
|
|
0.83* |
[0.68, 1.02] |
0.83* |
[0.67, 1.03] |
Health behaviours and condition |
Smoke tobacco (No) |
|
|
|
|
0.69 |
[0.48, 0.99] |
Drink alcohol (No) |
|
|
|
|
0.64 |
[0.45, 0.90] |
Proper health behaviour (No) |
|
|
|
|
0.84 |
[0.69, 1.03] |
Has annual health check (No) |
|
|
|
|
0.82 |
[0.65, 1.04] |
Self-rated poor health (Good) |
|
|
|
|
2.34*** |
[1.84, 2.97] |
Vision impairment (No) |
|
|
|
|
1.41*** |
[1.16, 1.72] |
Hearing impairment (No) |
|
|
|
|
1.41** |
[1.04, 1.93] |
Experience incontinence (No) |
|
|
|
|
1.71*** |
[1.35, 2.16] |
Experienced 1+ depressive symptom (No) |
|
|
|
|
1.69*** |
[1.36, 2.09] |
Poor cognitive performance (Good cognitive performance) |
|
|
|
|
1.67** |
[1.22, 2.30] |
|
ADL |
Variable (Reference) |
Model 1 |
Model 2 |
Model 3 |
RRR |
95% CI |
RRR |
95% CI |
RRR |
95% CI |
Region (Bangkok) |
|
|
|
|
|
|
Central [exc. Bangkok] |
0.79* |
[0.49, 1.28] |
0.62* |
[0.36, 1.06] |
0.58* |
[0.33, 1.02] |
North |
1.04 |
[0.64, 1.67] |
1.31 |
[0.70, 2.45] |
1.61 |
[0.85, 3.06] |
Northeast |
0.42** |
[0.25, 0.72] |
0.36*** |
[0.20, 0.66] |
0.39** |
[0.21, 0.72] |
South |
0.53** |
[0.28, 0.99] |
0.38** |
[0.19, 0.75] |
0.45** |
[0.22, 0.90] |
Sociodemographic factors |
Age |
|
|
1.11*** |
[1.08, 1.15] |
1.11*** |
[1.07, 1.14] |
Female (Male) |
|
|
2.32*** |
[1.46, 3.66] |
2.09** |
[1.32, 3.29] |
Urban residence (Rural) |
|
|
0.87* |
[0.57, 1.32] |
0.89* |
[0.57, 1.38] |
Marital status (Married) |
|
|
|
|
|
|
Widowed |
|
|
0.70 |
[0.44, 1.12] |
0.69 |
[0.43, 1.11] |
Separated/divorced/never married |
|
|
0.65 |
[0.31, 1.37] |
0.66 |
[0.30, 1.43] |
Living alone (Living with others) |
|
|
0.89 |
[0.47, 1.70] |
0.74 |
[0.39, 1.39] |
Higher than compulsory level (Compulsory level and below) |
|
|
0.79** |
[0.46, 1.36] |
0.95* |
[0.54, 1.65] |
Higher average annual income level (Lower income level) |
|
|
0.51** |
[0.33, 0.80] |
0.52** |
[0.33, 0.80] |
Income adequacy (Inadequate) |
|
|
0.46*** |
[0.31, 0.68] |
0.65** |
[0.43, 0.97] |
Employed in the past year (Not employed) |
|
|
0.39*** |
[0.24, 0.64] |
0.43*** |
[0.26, 0.70] |
Participated in community activities (No participation) |
|
|
0.43*** |
[0.27, 0.66] |
0.45*** |
[0.28, 0.70] |
Health behaviours and condition |
Smoke tobacco (No) |
|
|
|
|
0.85 |
[0.43, 1.67] |
Drink alcohol (No) |
|
|
|
|
0.44 |
[0.23, 0.83] |
Physically active (No) |
|
|
|
|
0.31 |
[0.21, 0.46] |
Proper health behaviour (No) |
|
|
|
|
0.78 |
[0.52, 1.17] |
Has annual health check (No) |
|
|
|
|
0.86 |
[0.55, 1.36] |
Self-rated poor health (Good) |
|
|
|
|
4.12*** |
[2.77, 6.13] |
Vision impairment (No) |
|
|
|
|
1.52** |
[1.03, 2.25] |
Hearing impairment (No) |
|
|
|
|
1.49* |
[0.92, 2.42] |
Experience incontinence (No) |
|
|
|
|
2.36*** |
[1.59, 3.50] |
Experienced 1+ depressive symptom (No) |
|
|
|
|
3.02*** |
[2.05, 4.45] |
Poor cognitive performance (Good cognitive performance) |
|
|
|
|
1.03 |
[0.62, 1.72] |
* p<0.1 ** p<0.05 *** p<0.001 |
Note: RRR= Relative risk ratio, CI = Confidence interval |
The sociodemographic and health behaviours and condition variables that were associated with functional limitation, IADL, and ADL were highly similar. Among the demographic variables, increasing age and being female were associated with the three categories of physical limitations. Socioeconomic and socialisation factors were also associated with the functional status outcomes where having lower education attainment and income levels were associated with the functional limitations, IADL, and ADL. This was similar for having a perceived inadequate income, non-employment, and non-participation in social activities in the community.
None of the health behaviours were significantly associated with the functional status outcomes but the health conditions were fairly similar. Self-rated poor health had the relative risk ratio of 2.4 for function limitations, 2.3 for IADL, and 4.1 for ADL. Having hearing or visual impairment, the experience of incontinence, and a symptom of depression were also associated with having physical limitations. A difference in observation was for IADL where it was associated with poor cognitive performance.
| Table 3: Model fit statistics from multinomial logit model of functional status |
|
Model 1 |
Model 2 |
Model 3 |
Wald Χ2 |
131.20*** |
1099.30*** |
1120.74*** |
McFadden's R2 |
0.01 |
0.15 |
0.18 |
AIC |
0.54 |
0.46 |
0.43 |
| * p<0.1 ** p<0.05 *** p<0.001 |
The addition of the sociodemographic variables and subsequently the health behaviours and conditions were statistically significant in explaining the variance of the outcome as observed through the Wald Χ2 (Table 3). It was observed that the inclusion of the sets of covariates improved the models as shown with the increasing values of the McFadden’s R2. To support this, the AIC was also examined and it was observed that Model 3 had the best model fit based on having the lowest value among the three models.
Discussion
The regional prevalence of physical limitation among older persons in Thailand was analysed in this study. It was found that functional limitations were less prevalent in the North, Northeast, South, and Central relative to Bangkok. IADL was more prevalent in Bangkok compared with the Central and the Northeast. There was no significant difference between Bangkok and the North, as well as with the South, in IADL prevalence level. Lastly, ADL was observed to be lower in prevalence in the Central, Northeast, and South regions than the capital city.
The observation in this study where more among the older persons with physical limitations were located in Bangkok is related to previous studies (9,21). Haque (21) created an index of active ageing where ADL was among the factors. It was identified that those in Bangkok had the lowest level of active ageing compared with the other administrative regions. In Khongboon et. al. (9), it was also identified that limitations were higher among those living in Bangkok compared to the South region. In comparison to the South though, the other regions had lower prevalence of limitations.
Bangkok is a highly distinct area from the rest of the country. The main economic sectors of Bangkok are manufacturing, retail trade, and financial activities (23). Central region has manufacturing and retail trade while North, Northeast, and South regions have predominantly agricultural sectors. Within this context, the education attainment, type of employment, and income level of the general and older population of Bangkok are also different (15). As such, there may be more among the older persons who report that they have physical limitations because they have the resources to cope with it. Having such resources also afford them of accessing healthcare facilities whereby despite having such higher levels of disabilities relative to other regions, older persons in Bangkok remain to have lower mortality levels (19). It has to be noted that a limitation of the current study is, due to the use of cross-sectional data, it cannot be determined whether an older individual lived in Bangkok before having physical limitations.
An aspect in the observation that was notable was that functional limitations, IADL, and ADL were more prevalent in the rural areas than in urban locations. Bangkok is an entirely urban area. As mentioned above, it is different from other regions; even among other urban locations in any of the other regions. To exemplify this, Chailurkit et. al. (24) observed that vitamin D deficiency was lower in rural than urban areas but, Bangkok had the highest level of deficiency. The conjecture was urbanisation leads to differences in lifestyle including people spending more time indoors among others.
The health conditions of the older individuals in the sample did not change the significance of the regional prevalence of physical limitations. It was also found that the inclusion of the health status into the analytical model was important. Evaluating an individual’s own health as poor and having vision and auditory impairment had been observed in other studies to have a negative effect on being engaged to physically activities (25). Incontinence has also been found to be associated with less physicality and having physical limitations (26,27). Depression symptoms have been found to affect self-efficacy of older people which can be a risk toward the deterioration of health (28). Poor cognitive performance was found to be different as it was only associated with IADL. This is because IADL is physical dimension of health but involves mental faculties to be performed such as counting (29).
As mentioned above, this present study has limitations such as using cross-sectional survey. Only associations between covariates were observed. I was also unable to determine if the disabilities were experienced prior their residence in the respective regions. Another limitation is that all measures utilised here are self-reported. Despite these constraints, it is important to consider the regional prevalence of functional status vis-à-vis the other individual characteristics. Understanding the health situation of the older population is vital for care policies in order to strengthen the health system in various locations of the country.
Acknowledgement
This work was done with support from the Population, Family Dynamics, and Social Policy research unit also at Chulalongkorn University.
References
- United Nations. 2019 Revision of World Population Prospects [Internet]. 2019 [cited 2019 Dec 6]. Available from: https://population.un.org/wpp/
- Solé-Auró A, Beltrán-Sánchez H, Crimmins EM. Are Differences in Disability-Free Life Expectancy by Gender, Race, and Education Widening at Older Ages? Popul Res Policy Rev. 2014;34(1).
- Karcharnubarn R, Rees P, Gould M. Healthy life expectancy changes in Thailand, 2002-2007. Heal Place. 2013 Nov 1;24:1-10.
- UNECE, European Commission. Active Ageing Index 2014: Analytical Report [Internet]. 2015 [cited 2020 Oct 6]. Available from: http://www.southampton.ac.uk/assets/sharepoint/groupsite/Administration/SitePublisher-document-store/Documents/aai_report.pdf
- Brown CJ, Flood KL. Mobility limitation in the older patient: A clinical review. JAMA - J Am Med Assoc. 2013 Sep 18;310(11):1168-77.
- Chatterji S, Byles J, Cutler DM, Seeman T, Verdes E. Health, functioning and disability in older adults - Present status and future implications. Lancet. 2015;385(9967):563–75.
- Fusco O, Ferrini A, Santoro M, Lo Monaco MR, Gambassi G, Cesari M. Physical function and perceived quality of life in older persons. Aging Clin Exp Res. 2012 Jul 31;24(1):68-73.
- Chuakhamfoo NN, Phanthunane P, Chansirikarn S, Pannarunothai S. Health and long-term care of the elderly with dementia in rural Thailand: A cross-sectional survey through their caregivers. BMJ Open. 2020 Mar 24;10(3):32637.
- Khongboon P, Pongpanich S, Chapman RS. Risk Factors for Six Types of Disability among the Older People in Thailand in 2002, 2007, and 2011. J Aging Res. 2016; Article ID 6475029. Available at https://www.hindawi.com/journals/jar/2016/6475029/
- Knodel J, Teerawichitchainan B, Pothisiri W. Caring for Thai Older Persons With Long-Term Care Needs. J Aging Health. 2018;30(10):1516-35.
- Vicerra PMM, Pothisiri W. Projecting health needs of late life adults in Thailand: Cognition-adjusted dependency and role of Education. J Public Heal Dev. 2020;18(2):37-57.
- Apinonkul B, Soonthorndhada K, Vapattanawong P, Jagger C, Aekplakorn W. Regional and gender differences in years with and without mobility limitation in the older population of Thailand. PLoS One. 2016 May 3;11(5):e0153763.
- Apinonkul B, Soonthorndhada K, Vapattanawong P, Aekplakorn W, Jagger C. Gender differences in health expectancies across the disablement process among older Thais. Zanetta DMT, editor. PLoS One. 2015 Mar 23;10(3):e0121310.
- Porell FW, Miltiades HB. Regional differences in functional status among the aged. Soc Sci Med. 2002 Apr 1;54(8):1181-98.
- Yiengprugsawan V, Carmichael GA, Lim LLY, Seubsman S ang, Sleigh AC. Has universal health insurance reduced socioeconomic inequalities in urban and rural health service use in Thailand? Heal Place. 2010 Sep 1;16(5):1030-37.
- Yan LD, Hanvoravongchai P, Aekplakorn W, Chariyalertsak S, Kessomboon P, Assanangkornchai S, et al. Universal coverage but unmet need: National and regional estimates of attrition across the diabetes care continuum in Thailand. Ikeda N, editor. PLoS One. 2020 Jan 15;15(1):e0226286.
- Vicerra PMM. Knowledge-behaviour gap on COVID-19 among older people in rural Thailand. Gerontol Geriatr Med. 2021;7:1-7.
- Tangcharoensathien V, Witthayapipopsakul W, Panichkriangkrai W, Patcharanarumol W, Mills A. Health systems development in Thailand: A solid platform for successful implementation of universal health coverage. Lancet. 2018 Mar 24;391(10126):1205-23.
- Aungkulanon S, Tangcharoensathien V, Shibuya K, Bundhamcharoen K, Chongsuvivatwong V. Post universal health coverage trend and geographical inequalities of mortality in Thailand. Int J Equity Health. 2016;15(1):1-12.
- College of Population Studies. A Report on the 2016 Population Change and Well-being in the Context of Ageing Society. Bangkok: Chulalongkorn University; 2018.
- Haque MN. Active Ageing Level of Older Persons: Regional Comparison in Thailand. J Aging Res. 2016; Article ID 9093018. Available at https://www.hindawi.com/journals/jar/2016/9093018/
- Pothisiri W, Vicerra PMM. Cognitive function, co-residence and social participation among older persons in Thailand. Soc Sci J. 2021; DOI: 10.1080/03623319.2020.1851076
- Office of the National Economic and Social Development Council. Gross Regional and Provincial Product Chain Volume Measure 2018 Edition [Internet]. Bangkok; 2020 [cited 2020 Nov 1]. Available from: https://www.nesdc.go.th/nesdb_en/ewt_w3c/ewt_dl_link.php?filename=national_account&nid=4317
- Chailurkit L, Aekplakorn W, Ongphiphadhanakul B. Regional variation and determinants of vitamin D status in sunshine-abundant Thailand. BMC Public Health. 2011 Nov 10;11(1):1-7.
- Hoppmann CA, Man Lee JC, Ziegelmann JP, Graf P, Khan KM, Ashe MC. Precipitation and physical activity in older adults: The moderating role of functional mobility and physical activity intentions. Journals Gerontol - Ser B Psychol Sci Soc Sci. 2017 Sep 1;72(5):792-800.
- Smith AL, Wang P-C, Anger JT, Mangione CM, Trejo L, Rodríguez L V., et al. Correlates of Urinary Incontinence in Community-Dwelling Older Latinos. J Am Geriatr Soc. 2010 Jun;58(6):1170-76.
- Townsend MK, Matthews CA, Whitehead WE, Grodstein F. Risk factors for fecal incontinence in older women. Am J Gastroenterol. 2013 Jan;108(1):113-19.
- McPhee JS, French DP, Jackson D, Nazroo J, Pendleton N, Degens H. Physical activity in older age: perspectives for healthy ageing and frailty. Biogerontology. 2016 Jun 1;17(3):567-80.
- Dodge HH, Kadowaki T, Hayakawa T, Yamakawa M, Sekikawa A, Ueshima H. Cognitive Impairment as a Strong Predictor of Incident Disability in Specific ADL-IADL Tasks Among Community-Dwelling Elders: The Azuchi Study. Gerontologist [Internet]. 2005 Apr 1 [cited 2020 Jan 20];45(2):222–30. Available from: https://academic.oup.com/gerontologist/article-lookup/doi/10.1093/geront/45.2.222
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