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The association of functional capacity with health-related behavior among urban home-dwelling older adults
Archives of Gerontology and Geriatrics 52 (2011) e11–e14
Contents lists available at ScienceDirect
Archives of Gerontology and Geriatrics journal homepage: www.elsevier.com/locate/archger
The association of functional capacity with health-related behavior among urban home-dwelling older adults Tommi Sulander a,b,* a b
Age Institute, Asemapa¨a¨lliko¨nkatu 7, FI-00520, Helsinki, Finland University of Helsinki, Department of Social studies, FI-00014 University of Helsinki, Finland
A R T I C L E I N F O
A B S T R A C T
Article history: Received 12 November 2009 Received in revised form 19 March 2010 Accepted 21 March 2010 Available online 20 April 2010
The present study was aimed to examine whether functional capacity among the urban home-dwelling older adults associates with health-related behavior. We also examined whether health-related behavior and certain diseases can be seen as mechanisms explaining socioeconomic disparities in functional capacity. A cross-sectional survey from 2008 was used to study 1395 older adults aged 75 and over living in one of the central areas of the city center of Helsinki, the capital of Finland. Associations of activities of daily living (ADL) with, smoking, food habits, physical activity, socioeconomic status and certain diseases were tested using ordinal regression model. Current smokers had slightly poorer functional ability than non-smokers among men. Those who did not use vegetables and/or fruits daily had a poorer functional capacity than daily users. Physically inactive respondents had clearly poorer functional capacity in comparison to active ones. Those with lower education had poorer functional status than higher educated irrespective of health-related behaviors and certain diseases. As health-related behaviors are modifiable, intervention programs should be targeted at all older adults with or without health problems. ß 2010 Elsevier Ireland Ltd. All rights reserved.
Keywords: Older adults Functional capacity Health-related behavior Socioeconomic status
1. Introduction Information on improving functional capacity among older adults is well documented in many western countries (Manton and Gu, 2001; Freedman et al., 2002; Ahacic et al., 2003; Crimmins, 2004; Sulander et al., 2006; Schoeni et al., 2008). A variety of factors have had an impact on this development (Stuck et al., 1999; Schoeni et al., 2008). One of the key factors are health-related behaviors such as smoking and physical activity, which have been found to have strong association with functioning (Stuck et al., 1999; Sulander et al., 2005; Schoeni et al., 2008). Previous evidence among older adults shows that former, and particularly current smoking have been associated with lower functional status (Stuck et al., 1999; Sulander et al., 2005). However, the poorer functional capacity among former smokers in comparison to never-smokers has suggested to be more related to chronic diseases than to the smoking history. A study from Finland showed that association between ex-smoking and poor functional capacity among older men vanished when controlling for various chronic diseases (Sulander et al., 2005). This indicates that some older men may have quit smoking due to these diseases.
* Tel.: +358 9 6122 1630; fax: +358 9 6122 1616. E-mail address: tommi.sulander@ikainst.fi. 0167-4943/$ – see front matter ß 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.archger.2010.03.018
Diet and functional capacity have not drawn much attention in previous research, even though, sufficient intake of energy and nutrient has an important part in efforts to prevent functional disabilities (Schroll, 2003). However, some studies have indicated those older adults following an unhealthy diet pattern to have somewhat poorer functional capacity than those with a healthy one (Rothenberg et al., 1994; Sulander et al., 2005). There is also evidence indicating no association between these factors (Sonn et al., 1998; Haveman-Nies et al., 2003). Physically active older adults have clearly better functional capacity compared to inactive ones (LaCroix et al., 1993; Young et al., 1995; Wang et al., 2002; Sulander et al., 2005). For older adults, regularity of the exercise is vital to attain health benefits (Mazzeo and Tanaka, 2001). Notwithstanding the apparent associations between functional capacity and health behavior, there is a lack of information on whether certain health behaviors are mediators explaining socioeconomic disparities in functional capacity. Some evidence suggests that occupational inequalities in functional capacity among older adults could partly be explained by health behavior and various diseases (Sulander et al., 2005). Such information may prove a vital contribution to the search for means to reduce health inequalities. For instance, studies from Finland have shown clear improvements in functional capacity among older adults (Martelin et al., 2002; Sulander et al., 2006). At the same time some of the health-related behaviors have changed into a healthier direction.
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T. Sulander / Archives of Gerontology and Geriatrics 52 (2011) e11–e14
The diet among older people has become healthier (Sulander et al., 2003) and smoking among older men has slightly decreased (Sulander et al., 2004). Nevertheless, differences between subgroups still exist. Those older adults with lower socioeconomic position have poorer functional capacity (Sulander et al., 2006) and diet (Sulander et al., 2003) than those with a higher position. The main purpose of this study was to determine whether functional capacity among the urban home-dwelling older adults associates with certain health-related behaviors, namely smoking, food habits and physical activity. We also examined whether healthrelated behavior and certain diseases can be seen as mechanisms explaining socioeconomic disparities in functional capacity. 2. Subjects and methods 2.1. Subjects and data collection This study is part of the ongoing Seniors in the City Project 2008–2010 conducted at the Age Institute in Finland. A crosssectional survey from 2008 was used to study all home-dwelling older adults aged 75 and over living in one of the central areas of the city center of Helsinki, the capital of Finland. The primary purpose of this survey is to obtain information about the state of health, functional capacity, quality of life, health-related behavior and coping with everyday life demands among these people. The total sample size was 1968 people. The average response rate was 71%; so that data from the questionnaires were used to study 1395 people (456 men and 939 women) aged 75–100 years. 2.2. Measures 2.2.1. Functional capacity To describe functional capacity we used 11 self-reported ADL items. These activities were: (1) use of stairs, (2) walking continuously 400 m, (3) handle matters outside home, (4) walking outside, (5) carrying heavy things, (6) cooking, (7) eating, (8) bathing, (9) dressing, (10) getting in and out of bed, (11) using toilet. Respondents were asked to assess their ability to perform these activities by choosing one of the following alternatives: ‘‘I cannot do this even with assistance’’, ‘‘yes, if someone assists me’’, I can perform it alone but it is difficult’’, ‘‘yes, alone without difficulty’’. The first three responses were combined as having difficulties in functional capacity. All 11 ADLs were summed up to produce a continuous scale ranging from 0 to 11 points. The higher the score, the poorer the functional capacity. Only those respondents who answered to all 11 ADLs were included in the analyses. 12% of the respondents were excluded because of insufficient ADL data. 2.2.2. Health-related behavior Smoking status was studied using three categories: current, exand never-smoker. As the number of daily smokers was very low, occasional smokers were included to the current smokers. On the basis of Finnish strategies to adjust food habits in a healthier direction (Pietinen et al., 2001; Puska, 2009), vegetable and fruit consumptions were used as indicators of healthy food habits. Dichotomized classifications for vegetable and fruit consumption were used in ordinal regression model. This was classified as 0 = not using fresh vegetables (including roots but excluding potato) or fruits (including berries) daily and 1 = using fresh vegetables and/or fruits daily. The question about physical activity was based on the frequency and duration of vigorous exercise. Older adults reporting exercise which causes breathlessness and sweating (>30 min per day) were classified as 0 = less than two times a week (physically inactive) and 1 = at least two times a week (physically active).
2.2.3. Other independent variables Education was dichotomized into two categories. The first category included respondents who were graduated from secondary school. The second category included respondents who had a background of middle school, elementary school or less than elementary school. Mainly for control purposes two additional variables were formed. Based on the question: ‘‘In the past year, have you been diagnosed with or treated for the following illnesses by a doctor’’, two dichotomous variables were constructed to indicate whether the subject suffered from cardiovascular diseases (CVD) (high blood pressure/hypertension, angina pectoris/coronary disease, cerebral infarction, ischemic attack, diabetes) or musculoskeletal diseases (MSD) (rheumatoid arthritis, arthrosis, degenerative disk disease/other back illness, osteoporosis). Disease variables were dichotomized as: 0 = no disease present and 1 = one or more diseases present. 2.3. Statistical methods The simultaneous contribution of several factors to functional capacity was examined by means of an ordinal regression method using the SPSS statistical program. The results are presented as cumulative odds ratios (COR) with 95% confidence intervals (CI). Cumulative models examine the relations between the categories of an ordinal dependent variable. Thus, COR expresses the incidence of upper values of the dependent variable compared to the lower values in various categories of independent variables. Table 1 Distribution (%) of functional capacity and background factors by age and gender. Age-groups
Number
Men
Women
75–79 80–84 85+ Total 75–79 80–84 85+
Total
226
939
141
89
456
333
309
297
Functional capacity No limitations One limitation Two limitations Three limitations Four limitations Five limitations Six limitations Seven limitations Eight limitations Nine limitations Ten limitations Eleven limitations
62.9 13.7 6.8 3.4 4.4 1.5 2.0 1.5 1.5 0.5 1.0 1.0
50.0 13.3 7.0 2.3 3.1 3.9 6.3 3.9 3.9 0.8 3.1 2.3
23.6 11.1 15.3 8.3 5.6 2.8 4.2 2.8 5.6 2.8 8.3 9.7
51.9 13.1 8.4 4.0 4.2 2.5 3.7 2.5 3.0 1.0 3.0 3.0
49.8 18.4 11.6 5.1 2.7 3.1 1.7 2.4 1.4 0.7 0.7 2.4
33.2 18.1 14.4 7.7 4.1 5.5 5.2 2.6 1.5 1.1 2.2 4.4
15.1 13.9 13.9 3.6 2.8 8.3 7.1 8.3 7.1 4.0 6.0 9.9
33.6 16.9 13.2 5.5 3.2 5.5 4.5 4.3 3.2 1.8 2.8 5.4
Education Secondary No secondary
55.3 44.7
60.7 39.2
62.5 37.5
58.4 41.6
49.7 50.3
44.8 55.2
42.4 57.6
45.8 54.2
Vegetable/fruit consumption Daily 48.2 48.2 Not daily 51.8 51.8
43.5 56.5
47.3 52.7
59.4 40.6
54.1 45.9
55.7 44.3
56.5 43.5
Smoking Non Ex Current
39.4 53.1 7.5
35.3 56.1 8.6
29.5 63.6 6.8
36.2 56.1 7.7
66.4 26.9 6.8
66.9 24.2 8.9
65.4 28.8 5.8
66.2 26.6 7.2
55.8
42.0
34.9
47.5
50.2
44.7
24.6
40.3
44.2
58.0
65.1
52.5
49.8
55.3
75.4
59.7
CVD Yes No
65.5 34.5
62.4 37.6
60.7 39.3
63.6 36.4
53.8 46.2
72.2 27.8
66.7 33.3
63.9 36.1
MSD Yes No
24.8 75.2
34.8 65.2
32.6 67.4
29.4 70.6
50.8 49.2
61.5 38.5
58.9 41.1
56.9 43.1
Physical activity At least 2 times per week Once a week or less
T. Sulander / Archives of Gerontology and Geriatrics 52 (2011) e11–e14
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Table 2 Ordinal regression with COR and their 95% CI for associations of functional capacity with health-related behaviors among men and women. Age-adjusted
+Education and health behaviors adjusted simultaneously
+CVD and MSD
1.00 1.89 (1.24–2.88) 5.48 (3.31–9.08)
1.00 1.83 (1.18–2.84) 5.39 (3.19–9.10)
1.00 1.70 (1.08–2.66) 5.74 (3.38–9.76)
Education Secondary No secondary
1.00 1.78 (1.22–2.60)
1.00 1.83 (1.24–2.71)
1.00 1.82 (1.22–2.70)
Vegetables/fruits Daily Not daily
1.00 1.45 (0.99–2.11)
1.00 1.36 (0.91–2.01)
1.00 1.41 (0.94–2.10)
Smoking Non Ex Current
1.00 1.08 (0.72–1.61) 2.03 (1.01–4.10)
1.00 0.93 (0.61–1.42) 1.53 (0.74–3.19)
1.00 0.87 (0.57–1.33) 1.54 (0.74–3.22)
Physical activity At least 2–3 times/week Once a week or less
1.00 2.68 (1.82–3.96)
1.00 2.80 (1.88–4.18)
1.00 2.77 (1.85–4.15)
1.00 2.00 (1.48–2.70) 5.90 (4.29–8.11)
1.00 1.96 (1.43–2.70) 5.16 (3.67–7.24)
1.00 1.67 (1.20–2.31) 4.75 (3.37–6.70)
Education Secondary No secondary
1.00 1.56 (1.21–2.00)
1.00 1.53 (1.17–1.99)
1.00 1.58 (1.21–2.06)
Vegetables/fruits Daily Not daily
1.00 1.76 (1.37–2.27)
1.00 1.55 (1.19–2.03)
1.00 1.53 (1.17–2.00)
Smoking Non Ex Current
1.00 1.19 (0.90–1.58) 0.90 (0.55–1.47)
1.00 1.11 (0.83–1.49) 0.84 (0.50–1.40)
1.00 1.02 (0.76–1.37) 0.83 (0.50–1.39)
Physical activity At least 2–3 times/week Once a week or less
1.00 2.89 (2.20–3.80)
1.00 2.79 (2.11–3.70)
1.00 2.78 (2.09–3.69)
Men Age (years) 75–79 80–84 85+
Women Age 75–79 80–84 85 +
For ordinal regression analyses three age-adjusted models were constructed. In model 1, each independent variable was studied individually in comparison to functional ability. In model 2, all health behaviors and education were examined simultaneously, while model 3 included education, health behaviors, CVD (inc. diabetes) and MSD. All analyses were calculated separately for men and women. 3. Results About half of the men and one-quarter of the women had no limitations in functional capacity, the proportion being lowest in the oldest age group (Table 1). Correspondingly, the proportion of those with more than one limitation in functional capacity was highest in the oldest age group. Every tenth of the respondents aged 85 and over had limitations in all 11 ADLs. The clearest age variation in background factors was seen in physical activity. The oldest respondents were less physically active than younger ones. Model 1 in Table 2 presents age-adjusted CORs showing the separate relationship of each independent variable with functional capacity. Those who had less than a secondary education had poorer functional capacity than those with at least secondary education. Poorer functioning was associated with infrequent vegetable or fruit consumption, especially among women. Current smokers among men reported poorer functional capacity than
never-smokers. The physically inactive had clearly worse functional capacity than active persons. When education and health-related behaviors were studied simultaneously in model 2, lower educated still had poorer functional capacity than higher educated. The disparities in functional capacity by consumption of vegetables and/or fruits diminished, but among women it remained statistically significant. The difference in functional capacity among male current and never-smokers vanished. Adjustment in model 2 had no effect on difference in functional capacity among physically active and inactive ones found in model 1. When chronic diseases were adjusted in addition to earlier factors (model 3), the results found in model 2 remained unattached. 4. Discussion The findings of this study indicated associations of functional capacity with health-related behaviors. Current smokers had slightly poorer functional ability than non-smokers among men. Those who did not use vegetables and fruits daily had a poorer functional capacity than daily users, especially among women. Physically inactive respondents had clearly poorer functional capacity in comparison to active ones. Those with lower education had poorer functional status than higher educated. Adjusting multiple factors did not narrow educational disparities in functional capacity.
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The response rate in the study was quite high, indicating high external validity of the findings. The sample was very selective including older adults only from one area of the city center of Helsinki. However, this sample was highly representative of this area as it consisted of all adults aged 75 and over living at home. The cross-sectional study design made it impossible to determine whether health-related behaviors were causes or consequences of the level of functional capacity. However, simultaneous adjustment of health behaviors and medical diagnoses gave important information on whether the association between functional ability and a certain variable was influenced by other factors. Current smoking has been found to be a predictor of functional decline (Stuck et al., 1999). Our results were partly in accordance with this. Among women the current smokers did not had poorer functional status than never-smokers. Half of the current smokers among women were occasional smokers, which might partly explain this result. It could be that occasional smoking did not have a heavy impact on functional status among older adults. Those who did not eat vegetables and/or fruits daily had poorer functional capacity than those consuming them daily, especially among women. This was in accordance with a previous study from Finland indicating older adults with a healthier diet to have better functional capacity (Sulander et al., 2003). Although the association between functional capacity and vegetable/fruit consumption weakened after adjusting for multiple factors, the result indicated the importance of this issue. As this is a practically unexplored area, further studies using various indicators of diet are required. Physical activity is a known predictor of better functional outcomes (LaCroix et al., 1993; Young et al., 1995; Wang et al., 2002). Our findings accorded with previous studies, as poorer functional capacity was clearly attached to inactivity. Furthermore, this association was alike independent of education, other health behaviors and chronic diseases as in previous Finnish study (Sulander et al., 2005). Previous studies have found a consistent association between socioeconomic status and functional capacity, indicating that the lower the status, the poorer the functional capacity (Arber and Cooper, 1999; Martelin et al., 2002; Sulander et al., 2006). It could be hypothesized that socioeconomic health differences can be explained, for example, by smoking and diet. However, our study indicated no changes in educational differences in functional capacity when other factors were controlled for. This is not in line with a previous study from Finland concerning older adults aged 65–79 years, which showed socioeconomic disparities in functional capacity to be partly explained by health behavior and various diseases (Sulander et al., 2005). One explanation for this discrepancy could be that health-related behavior and diseases do not play such important part in the level of functional capacity among people aged 75 and over as among younger older adults. Our finding may also suggest that several important explanatory factors generating educational disparities were not considered here, such as environmental and other than health behavioral influences. Functional capacity is a priority for preserving independence and maintaining better quality of life. Educational disparities in functional capacity continue to present a challenge to public health approaches aimed at reducing inequalities in health. Although healthy aging rests largely on lifetime’s accumulation, health-
related behavior changes in old age itself can also exert a marked impact on health. As these behaviors are modifiable, intervention programs should be targeted at all elderly people with or without health problems. Conflict of interest statement None. References Ahacic, K., Parker, M.G., Thorslund, M., 2003. Mobility limitations 1974–1991: period changes explaining improvement in the population. Soc. Sci. Med. 57, 2411–2422. Arber, S., Cooper, H., 1999. Gender differences in health in later life: the new paradox? Soc. Sci. Med. 48, 61–76. Crimmins, E.M., 2004. Trends in the health of the elderly. Annu. Rev. Public Health 25, 79–98. Freedman, V.A., Martin, L.G., Schoeni, R.F., 2002. Recent trends in disability and functioning among older adults in the United States: a systematic review. J. Am. Med. Assoc. 288, 3137–3146. Haveman-Nies, A., De Groot, L.C., Van Staveren, W.A., 2003. Survey in Europe on nutrition and the elderly: a concerted action study. Relation of dietary quality, physical activity, and smoking habits to 10-year changes in health status in older Europeans in the SENECA study. Am. J. Public Health 93, 318–323. LaCroix, A.Z., Guralnik, J.M., Berkman, L.F., Wallace, R.B., Satterfield, S., 1993. Maintaining mobility in late life. II. Smoking, alcohol consumption, physical activity, and body mass index. Am. J. Epidemiol. 137, 858–869. Manton, K.G., Gu, X., 2001. Changes in the prevalence of chronic disability in the United States black and nonblack population above age 65 from 1982 to 1999. Proc. Natl. Acad. Sci. U.S.A. 98, 6354–6359. Martelin, T., Koskinen, S., Kattainen, A., Sainio, P., Reunanen, A., Aromaa, A., 2002. Changes and differentials in the prevalence of activity limitations among Finns aged 65–74: comparison of the Mini-Finland Health Examination Survey (1978–80) and the FINRISK-97 Senior Survey (1997). Yearbook Popul. Res. Finland 38, 55–75. Mazzeo, R.S., Tanaka, H., 2001. Exercise prescription for the elderly. Current recommendations. Sports Med. 31, 809–818. Puska, P., 2009. General principles and intervention strategies. In: Puska, P., Vartiainen, E., Laatikainen, T., Jousilahti, P., Paavola, M. (Eds.), The North Karelia Project. From North Karelia to National Action. Helsinki University Printing House, Helsinki, pp. 27–48. Pietinen, P., Lahti-Koski, M., Vartiainen, E., Puska, P., 2001. Nutrition and cardiovascular disease in Finland since the early 1970s: a success story. J. Nutr. Health Aging 5, 150–154. Rothenberg, E., Bosaeus, I., Steen, B., 1994. Food habits, food beliefs and socioeconomic factors in an elderly population. Scand. J. Nutr. 38, 159–165. Schoeni, R.F., Freedman, V.A., Martin, L.G., 2008. Why is late-life disability declining? Milbank Q. 86, 47–89. Schroll, M., 2003. Aging, food patterns and disability. Forum. Nutr. 56, 256–258. Sonn, U., Rothenberg, E., Steen, B., 1998. Dietary intake and functional ability between 70 and 76 years of age. Aging (Milano) 10, 324–331. Stuck, A.E., Walthert, J.M., Nikolaus, T., Bula, C.J., Hohmann, C., Beck, J.C., 1999. Risk factors for functional status decline in community-living elderly people: a systematic literature review. Soc. Sci. Med. 48, 445–469. Sulander, T., Helakorpi, S., Rahkonen, O., Nissinen, A., Uutela, A., 2003. Changes and associations in healthy diet among the Finnish elderly, 1985–2001. Age Ageing 32, 394–400. Sulander, T., Helakorpi, S., Rahkonen, O., Nissinen, A., Uutela, A., 2004. Smoking and alcohol consumption among the elderly: trends and associations, 1985–2001. Prev. Med. 39, 413–418. Sulander, T., Martelin, T., Rahkonen, O., Nissinen, A., Uutela, A., 2005. Associations of functional ability with health-related behavior and body mass index among the elderly. Arch. Gerontol. Geriatr. 40, 185–199. Sulander, T., Martelin, T., Sainio, P., Rahkonen, O., Nissinen, A., Uutela, A., 2006. Trends and educational disparities in functional capacity among people aged 65–84 years. Int. J. Epidemiol. 35, 1255–1261. Wang, L., van Belle, G., Kukull, W.B., Larson, E.B., 2002. Predictors of functional change: a longitudinal study of nondemented people aged 65 and older. J. Am. Geriatr. Soc. 50, 1525–1534. Young, D.R., Masaki, K.H., Curb, J.D., 1995. Associations of physical activity with performance-based and self-reported physical functioning in older men: the Honolulu Heart Program. J. Am. Geriatr. Soc. 43, 845–854.
Contents lists available at ScienceDirect
Archives of Gerontology and Geriatrics journal homepage: www.elsevier.com/locate/archger
The association of functional capacity with health-related behavior among urban home-dwelling older adults Tommi Sulander a,b,* a b
Age Institute, Asemapa¨a¨lliko¨nkatu 7, FI-00520, Helsinki, Finland University of Helsinki, Department of Social studies, FI-00014 University of Helsinki, Finland
A R T I C L E I N F O
A B S T R A C T
Article history: Received 12 November 2009 Received in revised form 19 March 2010 Accepted 21 March 2010 Available online 20 April 2010
The present study was aimed to examine whether functional capacity among the urban home-dwelling older adults associates with health-related behavior. We also examined whether health-related behavior and certain diseases can be seen as mechanisms explaining socioeconomic disparities in functional capacity. A cross-sectional survey from 2008 was used to study 1395 older adults aged 75 and over living in one of the central areas of the city center of Helsinki, the capital of Finland. Associations of activities of daily living (ADL) with, smoking, food habits, physical activity, socioeconomic status and certain diseases were tested using ordinal regression model. Current smokers had slightly poorer functional ability than non-smokers among men. Those who did not use vegetables and/or fruits daily had a poorer functional capacity than daily users. Physically inactive respondents had clearly poorer functional capacity in comparison to active ones. Those with lower education had poorer functional status than higher educated irrespective of health-related behaviors and certain diseases. As health-related behaviors are modifiable, intervention programs should be targeted at all older adults with or without health problems. ß 2010 Elsevier Ireland Ltd. All rights reserved.
Keywords: Older adults Functional capacity Health-related behavior Socioeconomic status
1. Introduction Information on improving functional capacity among older adults is well documented in many western countries (Manton and Gu, 2001; Freedman et al., 2002; Ahacic et al., 2003; Crimmins, 2004; Sulander et al., 2006; Schoeni et al., 2008). A variety of factors have had an impact on this development (Stuck et al., 1999; Schoeni et al., 2008). One of the key factors are health-related behaviors such as smoking and physical activity, which have been found to have strong association with functioning (Stuck et al., 1999; Sulander et al., 2005; Schoeni et al., 2008). Previous evidence among older adults shows that former, and particularly current smoking have been associated with lower functional status (Stuck et al., 1999; Sulander et al., 2005). However, the poorer functional capacity among former smokers in comparison to never-smokers has suggested to be more related to chronic diseases than to the smoking history. A study from Finland showed that association between ex-smoking and poor functional capacity among older men vanished when controlling for various chronic diseases (Sulander et al., 2005). This indicates that some older men may have quit smoking due to these diseases.
* Tel.: +358 9 6122 1630; fax: +358 9 6122 1616. E-mail address: tommi.sulander@ikainst.fi. 0167-4943/$ – see front matter ß 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.archger.2010.03.018
Diet and functional capacity have not drawn much attention in previous research, even though, sufficient intake of energy and nutrient has an important part in efforts to prevent functional disabilities (Schroll, 2003). However, some studies have indicated those older adults following an unhealthy diet pattern to have somewhat poorer functional capacity than those with a healthy one (Rothenberg et al., 1994; Sulander et al., 2005). There is also evidence indicating no association between these factors (Sonn et al., 1998; Haveman-Nies et al., 2003). Physically active older adults have clearly better functional capacity compared to inactive ones (LaCroix et al., 1993; Young et al., 1995; Wang et al., 2002; Sulander et al., 2005). For older adults, regularity of the exercise is vital to attain health benefits (Mazzeo and Tanaka, 2001). Notwithstanding the apparent associations between functional capacity and health behavior, there is a lack of information on whether certain health behaviors are mediators explaining socioeconomic disparities in functional capacity. Some evidence suggests that occupational inequalities in functional capacity among older adults could partly be explained by health behavior and various diseases (Sulander et al., 2005). Such information may prove a vital contribution to the search for means to reduce health inequalities. For instance, studies from Finland have shown clear improvements in functional capacity among older adults (Martelin et al., 2002; Sulander et al., 2006). At the same time some of the health-related behaviors have changed into a healthier direction.
e12
T. Sulander / Archives of Gerontology and Geriatrics 52 (2011) e11–e14
The diet among older people has become healthier (Sulander et al., 2003) and smoking among older men has slightly decreased (Sulander et al., 2004). Nevertheless, differences between subgroups still exist. Those older adults with lower socioeconomic position have poorer functional capacity (Sulander et al., 2006) and diet (Sulander et al., 2003) than those with a higher position. The main purpose of this study was to determine whether functional capacity among the urban home-dwelling older adults associates with certain health-related behaviors, namely smoking, food habits and physical activity. We also examined whether healthrelated behavior and certain diseases can be seen as mechanisms explaining socioeconomic disparities in functional capacity. 2. Subjects and methods 2.1. Subjects and data collection This study is part of the ongoing Seniors in the City Project 2008–2010 conducted at the Age Institute in Finland. A crosssectional survey from 2008 was used to study all home-dwelling older adults aged 75 and over living in one of the central areas of the city center of Helsinki, the capital of Finland. The primary purpose of this survey is to obtain information about the state of health, functional capacity, quality of life, health-related behavior and coping with everyday life demands among these people. The total sample size was 1968 people. The average response rate was 71%; so that data from the questionnaires were used to study 1395 people (456 men and 939 women) aged 75–100 years. 2.2. Measures 2.2.1. Functional capacity To describe functional capacity we used 11 self-reported ADL items. These activities were: (1) use of stairs, (2) walking continuously 400 m, (3) handle matters outside home, (4) walking outside, (5) carrying heavy things, (6) cooking, (7) eating, (8) bathing, (9) dressing, (10) getting in and out of bed, (11) using toilet. Respondents were asked to assess their ability to perform these activities by choosing one of the following alternatives: ‘‘I cannot do this even with assistance’’, ‘‘yes, if someone assists me’’, I can perform it alone but it is difficult’’, ‘‘yes, alone without difficulty’’. The first three responses were combined as having difficulties in functional capacity. All 11 ADLs were summed up to produce a continuous scale ranging from 0 to 11 points. The higher the score, the poorer the functional capacity. Only those respondents who answered to all 11 ADLs were included in the analyses. 12% of the respondents were excluded because of insufficient ADL data. 2.2.2. Health-related behavior Smoking status was studied using three categories: current, exand never-smoker. As the number of daily smokers was very low, occasional smokers were included to the current smokers. On the basis of Finnish strategies to adjust food habits in a healthier direction (Pietinen et al., 2001; Puska, 2009), vegetable and fruit consumptions were used as indicators of healthy food habits. Dichotomized classifications for vegetable and fruit consumption were used in ordinal regression model. This was classified as 0 = not using fresh vegetables (including roots but excluding potato) or fruits (including berries) daily and 1 = using fresh vegetables and/or fruits daily. The question about physical activity was based on the frequency and duration of vigorous exercise. Older adults reporting exercise which causes breathlessness and sweating (>30 min per day) were classified as 0 = less than two times a week (physically inactive) and 1 = at least two times a week (physically active).
2.2.3. Other independent variables Education was dichotomized into two categories. The first category included respondents who were graduated from secondary school. The second category included respondents who had a background of middle school, elementary school or less than elementary school. Mainly for control purposes two additional variables were formed. Based on the question: ‘‘In the past year, have you been diagnosed with or treated for the following illnesses by a doctor’’, two dichotomous variables were constructed to indicate whether the subject suffered from cardiovascular diseases (CVD) (high blood pressure/hypertension, angina pectoris/coronary disease, cerebral infarction, ischemic attack, diabetes) or musculoskeletal diseases (MSD) (rheumatoid arthritis, arthrosis, degenerative disk disease/other back illness, osteoporosis). Disease variables were dichotomized as: 0 = no disease present and 1 = one or more diseases present. 2.3. Statistical methods The simultaneous contribution of several factors to functional capacity was examined by means of an ordinal regression method using the SPSS statistical program. The results are presented as cumulative odds ratios (COR) with 95% confidence intervals (CI). Cumulative models examine the relations between the categories of an ordinal dependent variable. Thus, COR expresses the incidence of upper values of the dependent variable compared to the lower values in various categories of independent variables. Table 1 Distribution (%) of functional capacity and background factors by age and gender. Age-groups
Number
Men
Women
75–79 80–84 85+ Total 75–79 80–84 85+
Total
226
939
141
89
456
333
309
297
Functional capacity No limitations One limitation Two limitations Three limitations Four limitations Five limitations Six limitations Seven limitations Eight limitations Nine limitations Ten limitations Eleven limitations
62.9 13.7 6.8 3.4 4.4 1.5 2.0 1.5 1.5 0.5 1.0 1.0
50.0 13.3 7.0 2.3 3.1 3.9 6.3 3.9 3.9 0.8 3.1 2.3
23.6 11.1 15.3 8.3 5.6 2.8 4.2 2.8 5.6 2.8 8.3 9.7
51.9 13.1 8.4 4.0 4.2 2.5 3.7 2.5 3.0 1.0 3.0 3.0
49.8 18.4 11.6 5.1 2.7 3.1 1.7 2.4 1.4 0.7 0.7 2.4
33.2 18.1 14.4 7.7 4.1 5.5 5.2 2.6 1.5 1.1 2.2 4.4
15.1 13.9 13.9 3.6 2.8 8.3 7.1 8.3 7.1 4.0 6.0 9.9
33.6 16.9 13.2 5.5 3.2 5.5 4.5 4.3 3.2 1.8 2.8 5.4
Education Secondary No secondary
55.3 44.7
60.7 39.2
62.5 37.5
58.4 41.6
49.7 50.3
44.8 55.2
42.4 57.6
45.8 54.2
Vegetable/fruit consumption Daily 48.2 48.2 Not daily 51.8 51.8
43.5 56.5
47.3 52.7
59.4 40.6
54.1 45.9
55.7 44.3
56.5 43.5
Smoking Non Ex Current
39.4 53.1 7.5
35.3 56.1 8.6
29.5 63.6 6.8
36.2 56.1 7.7
66.4 26.9 6.8
66.9 24.2 8.9
65.4 28.8 5.8
66.2 26.6 7.2
55.8
42.0
34.9
47.5
50.2
44.7
24.6
40.3
44.2
58.0
65.1
52.5
49.8
55.3
75.4
59.7
CVD Yes No
65.5 34.5
62.4 37.6
60.7 39.3
63.6 36.4
53.8 46.2
72.2 27.8
66.7 33.3
63.9 36.1
MSD Yes No
24.8 75.2
34.8 65.2
32.6 67.4
29.4 70.6
50.8 49.2
61.5 38.5
58.9 41.1
56.9 43.1
Physical activity At least 2 times per week Once a week or less
T. Sulander / Archives of Gerontology and Geriatrics 52 (2011) e11–e14
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Table 2 Ordinal regression with COR and their 95% CI for associations of functional capacity with health-related behaviors among men and women. Age-adjusted
+Education and health behaviors adjusted simultaneously
+CVD and MSD
1.00 1.89 (1.24–2.88) 5.48 (3.31–9.08)
1.00 1.83 (1.18–2.84) 5.39 (3.19–9.10)
1.00 1.70 (1.08–2.66) 5.74 (3.38–9.76)
Education Secondary No secondary
1.00 1.78 (1.22–2.60)
1.00 1.83 (1.24–2.71)
1.00 1.82 (1.22–2.70)
Vegetables/fruits Daily Not daily
1.00 1.45 (0.99–2.11)
1.00 1.36 (0.91–2.01)
1.00 1.41 (0.94–2.10)
Smoking Non Ex Current
1.00 1.08 (0.72–1.61) 2.03 (1.01–4.10)
1.00 0.93 (0.61–1.42) 1.53 (0.74–3.19)
1.00 0.87 (0.57–1.33) 1.54 (0.74–3.22)
Physical activity At least 2–3 times/week Once a week or less
1.00 2.68 (1.82–3.96)
1.00 2.80 (1.88–4.18)
1.00 2.77 (1.85–4.15)
1.00 2.00 (1.48–2.70) 5.90 (4.29–8.11)
1.00 1.96 (1.43–2.70) 5.16 (3.67–7.24)
1.00 1.67 (1.20–2.31) 4.75 (3.37–6.70)
Education Secondary No secondary
1.00 1.56 (1.21–2.00)
1.00 1.53 (1.17–1.99)
1.00 1.58 (1.21–2.06)
Vegetables/fruits Daily Not daily
1.00 1.76 (1.37–2.27)
1.00 1.55 (1.19–2.03)
1.00 1.53 (1.17–2.00)
Smoking Non Ex Current
1.00 1.19 (0.90–1.58) 0.90 (0.55–1.47)
1.00 1.11 (0.83–1.49) 0.84 (0.50–1.40)
1.00 1.02 (0.76–1.37) 0.83 (0.50–1.39)
Physical activity At least 2–3 times/week Once a week or less
1.00 2.89 (2.20–3.80)
1.00 2.79 (2.11–3.70)
1.00 2.78 (2.09–3.69)
Men Age (years) 75–79 80–84 85+
Women Age 75–79 80–84 85 +
For ordinal regression analyses three age-adjusted models were constructed. In model 1, each independent variable was studied individually in comparison to functional ability. In model 2, all health behaviors and education were examined simultaneously, while model 3 included education, health behaviors, CVD (inc. diabetes) and MSD. All analyses were calculated separately for men and women. 3. Results About half of the men and one-quarter of the women had no limitations in functional capacity, the proportion being lowest in the oldest age group (Table 1). Correspondingly, the proportion of those with more than one limitation in functional capacity was highest in the oldest age group. Every tenth of the respondents aged 85 and over had limitations in all 11 ADLs. The clearest age variation in background factors was seen in physical activity. The oldest respondents were less physically active than younger ones. Model 1 in Table 2 presents age-adjusted CORs showing the separate relationship of each independent variable with functional capacity. Those who had less than a secondary education had poorer functional capacity than those with at least secondary education. Poorer functioning was associated with infrequent vegetable or fruit consumption, especially among women. Current smokers among men reported poorer functional capacity than
never-smokers. The physically inactive had clearly worse functional capacity than active persons. When education and health-related behaviors were studied simultaneously in model 2, lower educated still had poorer functional capacity than higher educated. The disparities in functional capacity by consumption of vegetables and/or fruits diminished, but among women it remained statistically significant. The difference in functional capacity among male current and never-smokers vanished. Adjustment in model 2 had no effect on difference in functional capacity among physically active and inactive ones found in model 1. When chronic diseases were adjusted in addition to earlier factors (model 3), the results found in model 2 remained unattached. 4. Discussion The findings of this study indicated associations of functional capacity with health-related behaviors. Current smokers had slightly poorer functional ability than non-smokers among men. Those who did not use vegetables and fruits daily had a poorer functional capacity than daily users, especially among women. Physically inactive respondents had clearly poorer functional capacity in comparison to active ones. Those with lower education had poorer functional status than higher educated. Adjusting multiple factors did not narrow educational disparities in functional capacity.
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The response rate in the study was quite high, indicating high external validity of the findings. The sample was very selective including older adults only from one area of the city center of Helsinki. However, this sample was highly representative of this area as it consisted of all adults aged 75 and over living at home. The cross-sectional study design made it impossible to determine whether health-related behaviors were causes or consequences of the level of functional capacity. However, simultaneous adjustment of health behaviors and medical diagnoses gave important information on whether the association between functional ability and a certain variable was influenced by other factors. Current smoking has been found to be a predictor of functional decline (Stuck et al., 1999). Our results were partly in accordance with this. Among women the current smokers did not had poorer functional status than never-smokers. Half of the current smokers among women were occasional smokers, which might partly explain this result. It could be that occasional smoking did not have a heavy impact on functional status among older adults. Those who did not eat vegetables and/or fruits daily had poorer functional capacity than those consuming them daily, especially among women. This was in accordance with a previous study from Finland indicating older adults with a healthier diet to have better functional capacity (Sulander et al., 2003). Although the association between functional capacity and vegetable/fruit consumption weakened after adjusting for multiple factors, the result indicated the importance of this issue. As this is a practically unexplored area, further studies using various indicators of diet are required. Physical activity is a known predictor of better functional outcomes (LaCroix et al., 1993; Young et al., 1995; Wang et al., 2002). Our findings accorded with previous studies, as poorer functional capacity was clearly attached to inactivity. Furthermore, this association was alike independent of education, other health behaviors and chronic diseases as in previous Finnish study (Sulander et al., 2005). Previous studies have found a consistent association between socioeconomic status and functional capacity, indicating that the lower the status, the poorer the functional capacity (Arber and Cooper, 1999; Martelin et al., 2002; Sulander et al., 2006). It could be hypothesized that socioeconomic health differences can be explained, for example, by smoking and diet. However, our study indicated no changes in educational differences in functional capacity when other factors were controlled for. This is not in line with a previous study from Finland concerning older adults aged 65–79 years, which showed socioeconomic disparities in functional capacity to be partly explained by health behavior and various diseases (Sulander et al., 2005). One explanation for this discrepancy could be that health-related behavior and diseases do not play such important part in the level of functional capacity among people aged 75 and over as among younger older adults. Our finding may also suggest that several important explanatory factors generating educational disparities were not considered here, such as environmental and other than health behavioral influences. Functional capacity is a priority for preserving independence and maintaining better quality of life. Educational disparities in functional capacity continue to present a challenge to public health approaches aimed at reducing inequalities in health. Although healthy aging rests largely on lifetime’s accumulation, health-
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