Volunteer Participation at Young, Middle, Older Adulthood

J Pop Research (2012) 29:373–398 DOI 10.1007/s12546-012-9092-7

Participation in different types of volunteering at young, middle and older adulthood
Edith Gray • Siew-Ean Khoo • Anna Reimondos

Published online: 4 August 2012 Ó Springer Science & Business Media B.V. 2012

Abstract Around 35 % of Australian adults volunteer. It has been found that participation in volunteering varies with life course stage: people tend to participate less in early adulthood, which has been referred to as a ‘demographically dense’ period, and more in middle adulthood, which has been characterized as a more stable period of life. This paper extends this research to investigate the types of organizations for which people volunteer at different life course stages. This paper uses data from the Negotiating the Life Course project (2003 and 2006) to examine participation in volunteering for different types of organizations. The focus is on the type of organizations for which people volunteer and how that differs in young, middle and older adulthood. There are three dominant types of organizations that people volunteer for: welfare and community, sport and recreation, and education and training, and volunteering with each of these groups varies with a person’s life course stage. Younger adults tend to be more likely to volunteer for religious groups. People in middle adulthood, and particularly those with school-aged children, tend to volunteer in sport and recreation groups and education and training organizations, and volunteering with welfare, community and health organizations is dominant in older adulthood. Keywords Volunteering Á Civic participation Á Life course Á Welfare and community Á Sport and recreation Á Education and training

E. Gray (&) Á S.-E. Khoo Á A. Reimondos The Australian Demographic and Social Research Institute (ADSRI), The Australian National University, Building No. 9, Acton, ACT 0200, Australia e-mail: [e-mail]

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Introduction Volunteers make an important contribution to Australian society. There has been a long history of this type of civic participation in Australia, and in recent years there has been an increase in the percentage of people involved in volunteering (ABS 2008; FaHCSIA 2008). According to the Australian Bureau of Statistics, in 2006 the percentage of the Australian adult population that volunteered was 36 % (ABS 2011a). Volunteer work has economic and social benefits for society, and there is considerable evidence that the contributions volunteers make are beneficial to the volunteers as well as those they help (Li and Ferraro 2006; Musick et al. 1999; Thoits and Hewitt 2001). In understanding volunteering, two of the most important questions are ‘who does it?’ and ‘where do they do it?’ (Bussell and Forbes 2002). We already know at a general level quite a lot from previous studies about people who volunteer. For example we know that in Australia, volunteers are more likely to be female, to have higher levels of education and income, to be more religious and to have been born in Australia. Life cycle stage is also important: volunteering is particularly prevalent among individuals aged in their 30s and 40s with dependent children (ABS 2007). While we know about these general characteristics of volunteers, we know less about whether people volunteer for different types of organizations at different life course stages, and what types of people are more likely to volunteer for particular types of organizations. In this paper, we examine volunteering for different types of groups and organizations at three life course stages: young, middle and older adulthood; and we investigate the socio-demographic characteristics of people to determine who participates in volunteering for different organization types. The paper focuses on involvement in ‘formal’ volunteering, which is defined as an act of providing time to not-for-profit, charitable and community groups and organizations (Volunteering Australia 2005). It excludes time given to caring activities and similar ‘informal’ activities. The Australian Bureau of Statistics (2011a, p. 3) defines a volunteer as someone who ‘willingly gave unpaid help, in the form of time, service or skills, through an organization or group’ and this is the definition used in this paper.

Literature review Current knowledge about the characteristics of volunteers in Australia (ABS 2008) shows that the following groups are more likely to volunteer: (1) women; (2) employed men; (3) part-time employed women; (4) healthy people; (5) people who live outside capital cities; (6) people with young children and (7) people aged over 55. ABS data also showed that in 2010 the participation rate in volunteering was higher for people with degree or diploma qualifications and people born in Australia (ABS 2011a). According to a recent study, about 30 % of young adults at ages 18–24 and 25–34 did some volunteering, with those aged 18–24 having higher median hours volunteered, about 50 hours per year, compared with the 25–34 age group, 40 hours per year (FaHCSIA 2008). For young men there is little difference

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in volunteering hours across the two age groups, but for women there is a considerable drop at ages 25–34. The same study also showed that young adults are less likely to volunteer and they volunteer for fewer hours than people in middle adulthood although they are more likely to volunteer than people in later adulthood, but volunteer for fewer hours (FaHCSIA 2008). While the study shows that the volunteering rate was highest in middle adulthood, there are differences between men and women (FaHCSIA 2008). For women, the rate peaked in the age group 35–44, with almost 50 % volunteering in 2006, declining to less than 40 % in the age group 45–54. For men, the rate was about 40 % in both the 35–44 and 45–54 age groups. While the median hours for women were relatively stable in both age groups (around 55 per year), for men the median hours were less in the 35–44 age group than in the 45–54 age group, about 35 compared to 55). Participation rates in volunteering in Australia decline steadily from age 55. However, the hours volunteered are actually highest in the ages 65–84, for those people who volunteer (ABS 2007). So while those in later adulthood are less likely to volunteer, those who do volunteer contribute many hours, and studies have shown that older volunteers are more committed (Lyons and Hocking 2000; Zappala and Burrell 2002). Studies in Australia and other countries have also suggested that volunteering may have health, social and psychological benefits for older people and that their volunteer work is an important resource for non-profit organizations (Battaglia and Metzer 2000; Onyx and Warburton 2003; Van Willigen 2000; Warburton and Cordingley 2004). The General Social Survey conducted in 2010 by the Australian Bureau of Statistics shows that volunteering with sports and recreation groups was the most likely among Australian residents aged 35–54 with 20 % of people in that age range volunteering with such groups compared with 10 % or less among younger adults aged under 25 and 14 % in the age group 55–64 (ABS 2011b). In contrast, volunteering with welfare and community groups tended to increase with age, from 5 % in the age group 25–34 to 9 % in the age group 45–54 and reaching 14 % in the age group 65–74, while volunteering with religious groups was higher among the young (aged 18–24) and older age groups (aged 55–74) and lower in the age group 25–34. The pattern of volunteering in Australia shows some similarities to but also differences from those in other countries. A study of volunteering in the United States by Musick and Wilson (2008) shows that the rate of volunteering is highest in middle adulthood, as it is in Australia. However, people in the United States are most likely to volunteer for religious organizations (Bureau of Labor Statistics 2012), which differs from Australia where people are most likely to volunteer for sport and physical recreation groups (ABS 2010).

Theoretical framework and research questions Life course stage and volunteering The life course perspective is an extremely useful framework for investigating where people volunteer, because it examines involvement in volunteering for a

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specific type of organization in the context of a person’s life situation. The life course perspective has five general principles: life-span development, or studying lives over time which provides rich information; agency as the construction of lives and interaction with social and structural constraints; time and place emphasizes that historical context matters; timing suggests that it matters when life events occur in the life course; and linked lives highlight interaction with ‘important others’ (Elder et al. 2004). An important concept in understanding life course research is that age is an ‘empty indicator’ (Musick and Wilson 2008, p. 221). So while age is often used as a proxy for life stage, it is not a person’s age per se that is associated with behaviour, it is the circumstances which are associated with a person at that age, and in that context, which are important in understanding behaviour (Settersen 2009). In using a life course perspective, we need to examine the life events or circumstances associated with each life course stage, and how these can affect volunteering. The following outlines the three life course stages which this paper considers, and describes the associated dominant life events. Young adulthood In studying participation in volunteering, the first relevant life course stage is that of young adulthood. Young adulthood is generally represented by those in their late teens to late twenties or early thirties. The life course perspective emphasizes time in individual lives. By focusing on life course stage we are able to consider the other important events and conditions that individuals experience. Hence, there are times in people’s lives where there are many demands and at these times people may be less likely to volunteer; this is consistent with role overload theory (Rotolo 2000; Wilson 2000). In considering how this applies to young people who are in transition to adulthood, this time of life has been described as ‘demographically dense’ (Rindfuss 1991): a time when multiple transitions are being made, such as leaving education, starting work, leaving home, starting relationships and having families (Oesterle et al. 2004; Stoker and Jennings 1995). We may expect that people in young adulthood are less likely to volunteer because of these events occurring at this stage in their lives. Middle adulthood Middle adulthood is characterized as a more stable period of life (Musick and Wilson 2008). During these years many people have paid work and a large proportion have children, many of whom are of school age. At this life course stage, men are much more likely to be involved in full-time work, while women are likely to be in part-time work because they are more likely to have primary responsibility for childrearing activities. Employment has contradictory effects on participation in volunteering. It is thought that people who work have less time available to volunteer, but they may also have more social ties or opportunities for volunteering. There is evidence that part-time work is associated with a higher participation in volunteering (Wilson 2000). Having children in the household can be a constraint

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on volunteering, but can also provide opportunities for volunteering (Wilson 2000). It has been found that when pre-school aged children are present, people are less likely to volunteer, but it is not known whether this is also associated with the type of volunteering that they do. Where respondents have a school-aged child there is greater involvement, and there is some evidence that this is related to volunteering for education and sport organizations. The work and family circumstances of men and women at this life course stage can therefore affect their participation in volunteering and in the type of volunteering activity. For people with partners, another factor associated with their likelihood of volunteering at this life course stage is whether their partner volunteers. Life course theory recognizes that it is important to consider the effect that ‘significant others’ may have on behaviour. In the case of volunteering, there is some evidence that whether individuals volunteer is related to whether their spouses volunteer (Rotolo and Wilson 2006). The same study also found that wives had more influence on their husbands’ volunteering than vice versa. Later adulthood There are many life changes that occur in later ages that may play a role in understanding participation in volunteering and the type of volunteering activity. An important life course transition is retirement from employment. Changes in health and widowhood are also important transitions that may affect volunteering (Butrica et al. 2009; Hank and Erlinghagen 2009; Tang 2006). A study of volunteering by older people in Australia found that there was no difference in volunteering between those who were working and those who were retired; however, older people who volunteered were more likely to report better health and to come from higher occupational classes (Warburton et al. 1998). Moen and Fields (2002) refer to the ‘mid course’ years, distinguishing between people in the early stages of later life (their 50s, 60s and early 70s) and those at the oldest ages. Typically, these years are characterized by changes in role repertoire: often from a greater intensity in paid work. Goss (1999) also noted the very different participation rate in volunteering as people reached the ‘oldest old’ ages, which is related to health problems. It is important to distinguish between these role stages in later adulthood where possible. Using the life course framework People’s lives are dynamic: their ability and availability for volunteering changes depending on their situation. So too does the type of volunteering activity in which they participate and their motivations for volunteering. We argue that people will volunteer in organizations to which they relate, which is associated with life course stage. Recent research finds that there is substantial evidence that people are motivated to volunteer by psychological and social needs in addition to altruistic reasons (Dolnicar and Randle 2007). So for example, in addition to altruistic reasons, parents may become personally involved in volunteering for child activities because it is expected, while older people may do it for social contact, to feel useful

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or to occupy spare time (Bussell and Forbes 2002). In both cases, these motivations are a result of the life course stage of the individuals. It has been suggested that research on volunteering in Australia needs to be grounded in a theoretical framework that improves understanding of why people volunteer and the contextual factors that motivate volunteering (McDonald and Warburton 2001). The life course approach is one that should be examined further in relation to understanding the motivations for volunteering in Australia. In adopting this approach to examine participation in different types of volunteering in Australia, the current study aims to add to current understanding of the relationship between volunteering and other aspects of people’s lives. Research questions The broad aim of the paper is to examine the relationship between life course stage and type of volunteering to further understand the contextual factors in people’s life course experiences that motivate volunteering. The paper addresses the following specific research questions: What kinds of volunteering activity do people engage in during young, middle and later adulthood and how are they related to the person’s life course stage? Which demographic and socio-economic characteristics are associated with the different types of volunteering at the life course stages of young, middle and later adulthood? Is participation in different types of volunteering affected by life transition events in young, middle and later adulthood, such as partnering, having children and retirement?

Data and method Data The Negotiating the Life Course Survey (NLC) is a longitudinal social survey of individuals conducted every 3 years since 1996/1997 through to 2009. The original Wave 1 sample consisted of 2,231 persons aged 18–54 years living in Australia with a telephone number listed in the White Pages (McDonald et al. 2000). Because of the attrition of panel respondents over time, a top-up sample of 2,000 new respondents was included in Wave 4 (2006) to increase the sample size. In this topup sample those aged 18–26 were oversampled to increase the number of younger respondents.1 Wave 4 data (N = 3,138) are used in this investigation of where people volunteer. While the NLC sample was designed in Wave 1 to be broadly representative of the population aged 18–54 years living in Australia, with a telephone number listed in the White Pages, the sample is selective in a number of ways. The sample is somewhat biased towards women and towards older people (McDonald et al. 2000).
1

Survey weights adjust for sampling procedure.

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However these discrepancies in the age and sex structure of the sample, as compared to the general population, are corrected for in the sample weights. There is also an overrepresentation in the survey of people born in Australia, and people who have tertiary education. The weights do not correct for selectivity on these characteristics. The selectivity of the survey respondents on these characteristics is likely to overestimate the rate of participation in volunteering since the participation rate in volunteering is shown to be higher for people with degree or diploma qualifications and people born in Australia (ABS 2011a). In addition since we use data from Wave 4 of the survey, we may be including an overrepresentation of respondents who are more ‘civic-minded’, given that they have taken part in the survey since 1996/1997 whereas other respondents have dropped out over time. However, the selectivity of the NLC sample should not affect the results of the regression analyses which examine the relationship between individual respondents’ characteristics and their participation in volunteering with different types of groups and organizations. The series of questions in NLC about volunteering activities were developed to maximize people’s ability to recall past volunteering behaviour. Hall (2001, p. 518) notes that ‘it is useful to ask about specific behaviours rather than rely on a general question that is prone to subjective interpretation’. In Wave 4, NLC respondents were asked directly if they volunteered for a series of specific types of groups or organizations. This is an example of ‘aided recall’, i.e. respondents are asked about specific activities, rather than a general question. This helps respondents because ‘they are asked to recognize the event rather than engage in the more difficult task of recalling the event’ (Hall 2001, p. 520). Furthermore, with the use of multiple questions, ‘each question requires a search of memory and increases the possibility that associations will be triggered.’ Respondents were given a list of 11 different types of organizations (plus an ‘other option’)2 and were asked if they volunteered for each one of them. People were able to respond that they volunteered with different types of organizations. The NLC Survey question asks: In the last 12 months, have you done any unpaid voluntary work for any of the following organisations? [Voluntary work excludes ‘work for the dole’ programs].

2

This list overlaps with the International Classification of Non-Profit Organisations (ICNPO) in the United Nations Handbook on Non-Profit Institutions in the System of National Accounts (2003). Since the 11 groups are listed in the NLC Survey Questionnaire, it is not possible to regroup them into the categories of the ICNPO. The main differences between this list and the ICNPO major groupings are (1) culture and arts are grouped separately from sports and recreation whereas in the ICNPO they are all in major Group 1 as Culture and Recreation; (2) emergency services are grouped separately from welfare and community services whereas in the ICNPO they are all in major Group 4 as Social Services; (3) the ICNPO has a group called Philanthropic intermediaries and voluntarism promotion (Group 8), which is not listed in the NCL Survey and would be included in the ‘Other’ category; and (4) the ICNPO has a major group called Development and Housing (Group 6) which includes employment and training and social and community development. In the NLC Survey, training is included with ‘Education’, and social and community development is included in ‘Welfare/community’’. Aside from these differences, the other groups listed in the NLC survey questionnaire are similar to the other major groups in the ICNPO.

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Yes 1 2 3 4 5 6 7 8 9 10 11 Sport/recreation/hobby Welfare/community Health Emergency services Education/training/youth development Religious Environment Business/professional/union Law/justice/political Arts/culture Foreign/international Other organisation (specify) 1 1 1 1 1 1 1 1 1 1 1 1

No 2 2 2 2 2 2 2 2 2 2 2 2

Respondents are then asked the number of hours volunteered in total, but these are not used in this paper. Overall, 53 % of participants had volunteered for at least one organization in the last 12 months. This is higher than national estimates indicated in other data (ABS 2008, 2011a) and is likely to be due to the overrepresentation of people with more education and people born in Australia in the NLC sample, who are more likely to volunteer, as discussed earlier. As shown in Fig. 1, of the eleven different types of organizations included in the survey, the three most popular organizations to volunteer for were sport/recreation/ hobby, welfare/community and education/training/youth development. The remaining eight types of organizations attracted a much smaller percentage of respondents, generally less than 10 % with the exception of religious organizations (11 %). The distribution of volunteering across the different types of organizations in the NLC is

Fig. 1 Percentage of NLC respondents (Wave 4) who volunteered, by organization type

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very similar to the distribution observed in the survey of volunteers in 2006 conducted by the Australian Bureau of Statistics (FaHCSIA 2008). Method The analysis is conducted in three parts. At the first stage we conduct descriptive analysis of the characteristics of people who volunteer for each of the eleven different types of organizations. In the second part we use multivariate analysis to investigate patterns of volunteering for eight of the different types of organizations. We use logistic regression models for this multivariate analysis, which is of volunteering with eight types of organizations for which at least 5 % of respondents volunteered: sport, welfare/community, health, education, religious, environment and animal welfare, business and professional and arts/culture. Welfare/community and health organizations were combined into one category as the descriptive analysis indicated that the determinants of volunteering for these two types of organization were very similar. For each logistic regression model, the dependent variable was whether the respondent volunteered for that organization (No = 0, Yes = 1). Finally, we examine volunteering for the three main types of organizations (sport/recreation/hobby, welfare/community/health and education/ training/youth development) using a dynamic perspective. For this part of the analysis we include variables which describe life course transitions which may have taken place between Wave 3 and Wave 4 of the survey, focusing in particular on childbearing and employment changes. The analysis is conducted separately for those aged 25–54 years, for whom childbearing and rearing are particularly relevant, and for those aged 55–64 years old for whom retirement is relevant. This analysis includes a subsample of the Wave 4 sample (N = 914) that were also present in Wave 3.3 Variables The main variable of interest is age, which is a broad representation of life course stage. Participants in the NLC Survey were aged 18–64 in 2006, and we split these into five age categories. Young adults are represented by the age groups 18–24 and 25–34, middle adulthood is represented by age groups 35–44 and 45–54, and older adulthood is represented by the age group 55–64. We should note however, that in using these data we are not able to compare older adults aged 65? as they were not included in the NLC Survey. This means that we cannot examine volunteering by the ‘oldest old’ (as described by Goss 1999), but focus our attention on those adults in their mid-course years (as described by Moen and Fields 2002).

3

It is very rare that this type of transition analysis can be examined for volunteering. Volunteering information is rarely collected in longitudinal surveys, and we know of no other longitudinal survey which collects information on type of organization volunteered for. This analysis can only be conducted between Wave 3 and Wave 4 because the questions on volunteering are collected differently in earlier waves.

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As discussed earlier, it is not age alone that defines a life course stage, but also events or experiences which characterize those life stages; so other variables are also included to describe the different life course stages, which are described here: Relationship status differentiates between those who are single, married and cohabiting. For those who are married or cohabiting, the variable also contains information about whether their partners volunteer. Two dichotomous variables measure the presence of a pre-school aged child and a school-aged child in the household. Employment is also related to life course stage, as is whether employment is fulltime or part-time, particularly in the case of women. The employment variable has three categories: not employed, employed part-time and employed full-time. Caring for others can also be related to life course stage as people are more likely to provide care at certain times in their life than other times, and would have less time for volunteering. The caring variable is dichotomous, coded as 1 if someone provides care to any person with a disability or long-term illness, and zero otherwise. We control for a number of sociodemographic factors which are known to be associated with participation in volunteering, including highest education, religiosity, length of time lived at current address and country of birth. Education level is one of the most consistent and strongest predictors associated with participation in volunteering (Musick and Wilson 2008). It is thought that education may be linked to higher rates of volunteering through a number of pathways including increased self-confidence and awareness of social problems, but also through the fact that more educated people are more likely to have extensive social networks, which increases the chances that they will be asked to volunteer (Musick and Wilson 2008, pp. 119–120). However, while there is a clear association between education and volunteering at a general level, much less is known about possible educational differences in volunteering for different types of organization. There is some evidence that education may be more important for determining some types of volunteering compared to others (Wilson 2000). In this study the variable describing highest education is divided into five categories ranging from incomplete secondary schooling or less to having a university degree. Religion is another important predictor of volunteering. Although there are differences by types of religion and religious denomination, most religions encourage altruism and helping behaviour (Wilson and Janoski 1995). We measure religiosity rather than religious affiliation, using a question that asked respondents to indicate how important religion was in their lives. Four response categories were given including: very important, important, somewhat important and not important. In the multivariate analysis the ‘very important’ and ‘important’ categories were combined. Opportunities for volunteering are heightened if individuals have extensive social networks and have strong ties to the community. As a proxy for the strength of ties to the local community, we include a variable that measures how long respondents have been living in their current home (0–1 years, 2–5 years or 6? years). We note however that it is possible that respondents may have recently moved into a home, but may have been living in the same area, in which case their social ties to the

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community may be stronger than indicated. Hence this indicator is probably an underestimate of the true effect of community ties. Finally, we also examine the person’s country of birth using a variable that measures whether respondents were born in Australia, in another English-speaking country, or in a non-English-speaking country. While volunteers born outside of Australia may have opportunities to volunteer for organizations linked to their ethnic or religious groups, they may have fewer social ties than those born in Australia. For those born in non-English-speaking countries, language may be an additional barrier preventing them from volunteering in the wider community (Volunteering Australia 2007). For the third part of the analysis, we also include several variables which describe life course transitions. In particular we include a variable describing whether or not there has been a change in relationship status between Wave 3 and Wave 4, whether or not a child has been born between Wave 3 and Wave 4 and whether or not there has been a change in employment status between the two waves. Owing to the small number of people aged 55–64 who had pre-school or school-aged children living at home, all child-related independent variables are not included in the regression models for this age group. In this third part of the analysis we also grouped together those who had been living at their current address for 0–1 and 2–5 years because of the small number of cases that had recently moved among the subsample of interest, respondents present in both Wave 3 and Wave 4.

Results Descriptive Table 1 shows the percentage of respondents who volunteered for each of the eleven different types of organizations, according to the demographic and socio-economic characteristics discussed above. For three types of organizations in particular, Emergency services, Law/Justice/Political and Foreign/International, the percentage of respondents who volunteered was very small and it was difficult to find much differentiation in the characteristics of the respondents. We focus the discussion below on volunteering patterns for the three largest types of organizations: sport/recreation/ hobby, welfare/community and education/training and youth development. People who volunteer for sport and recreation organizations are more likely to have the following characteristics: male, aged 35–44, have partner who also volunteers, have a school aged child, and employed, either full- or part-time. The pattern by education is an inverted u-shape, with this type of volunteering being highest among those with a diploma or vocational qualification, and lower among those with a university degree or with no post-school qualification. Volunteering for sport/recreation and hobby organization is significantly higher for people who are less religious. People who have lived at their current home for six or more years are more likely to volunteer for this type of organization as are those born in Australia or another English-speaking country (23 %) compared to those born in a nonEnglish-speaking country (11 %).

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Table 1 Percentage of respondents who volunteered for each type of organization, by selected characteristics
Emergency services, % Education/ training/ youth dev., % *** 14 21 *** 3 4 4 5 5 *** *** *** *** *** 13 13 9 7 17 11 8 9 23 10 5 4 3 4 3 *** 12 12 6 5 4 20 13 6 3 2 * *** 7 6 3 5 7 *** 12 6 4 3 5 11 7 8 4 5 2 2 ** 2 3 1 3 2 ** 461 484 680 857 655 *** ** 1,169 1,968 Religious, % Environment and animal welfare, % Business/ professional union, % Law/ justice/ political, % Arts/ culture, % Foreign/ international, % Total in group, N

123
** 6 8 ** 8 7 5 7 10 3 6 *** 9 4 2 8 4 2 7 29 22 10 10 3 5 2 7 1 3 0 858 826 15 9 13 5 19 10 5 6 2 107 7 2 6 0 3 3 0 3 2 215 8 4 18 11 7 6 4 8 3 1,128

Variable

Sport/ recreation/ hobby, %

Welfare/ community, %

Health, %

Sex

***

Male

27

20

Female

20

21

Life course variables

Age group

***

***

18–24

17

17

25–34

15

18

35–44

30

18

45–54

29

22

55–65

19

27

Relationship and partner volunteering

***

***

***

Married, partner volunteers

42

32

Married, partner does not volunteer

12

10

Cohabiting, partner volunteers

37

33

Cohabiting, partner does not volunteer

10

12

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Single

18

19

Table 1 continued
Emergency services, % Education/ training/ youth dev., % *** 8 5 *** 5 3 *** 6 3 3 *** 6 4 *** 8 9 6 7 3 17 5 13 9 22 2 23 *** *** 17 11 9 10 9 7 6 7 18 11 18 12 12 6 16 12 7 23 13 7 5 4 ** 8 5 *** 9 10 4 4 14 10 7 8 *** *** 4 4 3 *** 6 3 *** 6 3 3 2 6 5 *** 8 6 4 6 2 2 *** 5 1 1 2 848 354 840 580 553 2,583 5 6 5 29 13 4 6 2 14 11 8 6 4 *** 3 20 9 5 5 4 2 ** 6 3 5 17 12 7 6 3 6 2 2 ** 3 1 * 2 3 2 1,302 966 282 2,490 643 2,688 446 Religious, % Environment and animal welfare, % Business/ professional union, % Law/ justice/ political, % Arts/ culture, % Foreign/ international, % Total in group, N

Variable

Sport/ recreation/ hobby, %

Welfare/ community, %

Health, %

Has a pre-school aged child

No

24

21

Yes

20

18

Has a school-aged child 8 4 * 6 8 9

***

***

No

21

21

Participation in different types of volunteering

Yes

34

18

Employment status

***

**

Employed fulltime

26

19

Employed parttime

23

21

Not employed

18

24

Provides care to someone 11 6

***

***

Yes

25

28

No

23

19

Background variables

Highest education

***

***

Bachelor degree?

22

27

Diploma

28

24

Vocational qual.

27

18

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Complete secondary

21

15

385

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Table 1 continued
Emergency services, % Education/ training/ youth dev., % 11 8 5 2 1 2 1 Religious, % Environment and animal welfare, % Business/ professional union, % Law/ justice/ political, % Arts/ culture, % Foreign/ international, % Total in group, N 512

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6 4 ** 6 10 8 6 * 5 15 2 8 5 3 4 19 4 7 6 2 5 15 12 7 7 4 3 24 50 6 6 6 8 4 4 5 *** *** ** 4 2 2 2 517 392 865 1,356 11 6 7 *** 7 7 7 7 4 17 1 10 17 12 6 21 12 4 18 11 ** 7 9 4 7 6 9 5 6 5 19 11 7 4 17 11 7 1 16 12 4 4 5 7 4 4 3 * 3 5 2 3 5 5 6 ** 5 9 4 5 2 2 2 *** 2 4 5 2 2,556 323 257 3,134 225 930 1,975

Variable

Sport/ recreation/ hobby, %

Welfare/ community, %

Health, %

Incomplete secondary or less

19

16

Importance of religion

**

***

Very important

18

30

Important

24

26

Somewhat important

25

19

Not important

25

16

Length of time lived at current address

***

0–1 years

16

20

2–5 years

19

18

6? years

27

22

Country of birth

***

Australia

25

20

English speaking

26

22

Other

9

19

Total

24

20

Source: NLC 2006

E. Gray et al.

* p \ 0.10; ** p \ 0.05; *** p \ 0.01

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In comparison people who volunteered for welfare, community and health organizations are different in many ways. They are more likely to be in the older age groups, (the percentage is highest in the group aged 55–64) and to not have a school-aged child living at home. They are also more likely not to be employed or providing care for someone who is ill or disabled. In contrast to volunteering for sport and recreation organizations, there is strong positive association between higher levels of education and volunteering for welfare and community groups. Also in contrast to sport and recreation, people volunteering for welfare or community groups are significantly more likely to be religious. Among those who state that religion is very important in their lives, 30 % volunteer for welfare and community groups, compared to 17 % of those who say that religion is not important. Volunteering for education, training and youth development groups appears to be strongly associated with middle adulthood when people have young children living at home. In addition to a strong gender difference, with higher rates of volunteering among females, we note that volunteering for this type of organization is highest among those aged 35–44 years old. Participation is also higher among those who are partnered, particularly married couples where both partners volunteer. People with a school-aged child are significantly more likely to be volunteering for this type of organization. Individuals who work part-time are the most likely to be involved with education and youth development groups, which may be associated with the greater propensity for women to volunteer for this type of organization. Again, we note a strong education gradient. Among those with a university degree, 23 % volunteer for an education, training or youth development organization, compared to 11 % of people with incomplete secondary schooling or less. Finally there also appears to be an association with religiosity, although the pattern is not as strong as it was for volunteering with welfare and community groups. Figure 2 compares the age pattern of volunteering for the different types of organization. For activities which may be related to children, including sport/

Fig. 2 Percentage of individuals volunteering for different types of organizations, by age group. Source: NLC 2006

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recreation/hobby and education/training/youth development, we observe a definite peak around middle adulthood when individuals are most likely to have young children living at home. For the other organizations, including religious groups, environment and animal welfare and arts and culture, the relationship with age is u-shaped, being higher among young and older adults but falling in middle adulthood. Finally, for welfare and community organizations there appears to be a strong increasing trend of participation after age 45. These age patterns are very similar to those observed in the 2010 General Social Survey (ABS 2011b) although the percentages are higher in each age group in the NLC Survey. Multivariate The results of the first multivariate analysis, shown in Table 2, largely support the results of the bivariate analysis discussed above. The association between the life course variables and volunteering for each of the different types of organization appears to be robust even after controlling for background characteristics such as highest education and country of birth. For sport/recreation/hobby volunteering we again observe a male bias, and significantly higher odds of volunteering among those aged 35–44. While individuals with spouses or cohabiting partners who volunteer are significantly more likely than single people to volunteer themselves, those who are partnered but whose partners do not volunteer are not more likely to volunteer than people who are single. Having a pre-school aged child is associated with a lower likelihood for this type of volunteering, but having a school-aged child is associated with much higher odds of volunteering for sport/recreation/hobby groups. Significantly, once other life course variables such as presence and age of children and socio-economic variables such as education are controlled in the regression analysis, there is no significant difference in the odds of volunteering with sport/recreation/hobby groups between young adults aged 18–24 and older adults aged 35–44 and 45–54, unlike the descriptive results shown in Table 1 and Fig. 2. This indicates that the higher percentage of individuals in middle adulthood volunteering with sport/recreation/hobby groups is very much related to their having school-aged children, who present an opportunity to parents to volunteer with their children’s sporting and other extracurricular activities. There is a higher likelihood of volunteering with welfare, community and health organizations among females, and among older adults who may be past the period of their lives where they are active in the labour force and have children living with them at home. Having a school-aged child has a strong effect on volunteering with education, training and youth development groups even after controlling for the other variables in the model. This suggests that volunteering for education/training/ youth development organizations is very much related to having a school-aged child, who provides the opportunity for this type of volunteering. Volunteering for religious organizations shows an interesting pattern in that there are higher odds of participating for those aged 18–24, controlling for other factors. None of the other life course variables shows a strong relationship with this type of volunteering. Unsurprisingly, an individual’s level of religiosity is strongly associated with this kind of volunteering.

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Table 2 Logistic regression of volunteering for specific types of organization (Odds ratios) Welfare, community and health Education, training, and youth dev. Religious Environment, animal welfare Business, professional, union Arts, culture

Sport, recreation, hobby

Sex Ref 1.22** 1.47*** 1.06 0.89 0.52*** Ref Ref Ref Ref Ref 1.13

Male (ref)

Ref

Female

0.67***

Life course variables 1.12 1.09 Ref 1.25 1.61*** Ref 1.63*** 0.43*** 2.12*** 0.47*** Ref 0.91 Ref 0.78* 1.03 Ref 2.86*** Ref 0.25*** 0.88 0.34*** 1.46*** Ref Ref 3.01*** 0.46*** 0.62 0.12*** Ref 0.64* Ref 0.98 0.81 1.09 0.82 0.97 1.45 1.33 Ref 1.67*** 0.27*** 2.60*** 0.69 Ref 0.93 Ref 0.51*** Ref Ref Ref 0.92 1.60* 1.05 1.19 2.27*** 0.97 0.74 1.27 Ref 2.11*** 1.83** Ref 1.11 0.36*** 0.86 0.48* Ref 1.36 Ref 1.06 1.32 1.21 Ref 1.21 1.82** Ref 1.04 0.13*** 0.62 0.49* Ref 0.59 Ref 0.86

Age group

18–24

0.82

25–34

0.73*

Participation in different types of volunteering

35–44 (ref)

Ref

45–54

0.83

55–64

0.63***

Relationship and partner volunteering

Single (ref)

Ref

Married, partner volunteers

3.48***

Married, partner does not volunteer

0.61***

Cohabiting, partner volunteers

2.97***

Cohabiting, partner does not volunteer

0.54**

Has a pre-school aged child

No (ref)

Ref

Yes

0.53***

Has a school aged child

No (ref)

Ref

Yes

1.61***

389

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Table 2 continued Welfare, community and health Education, training, and youth dev. Religious Environment, animal welfare Business, professional, union Arts, culture

123
Ref 1.09 1.39*** Ref 1.46*** 0.97 1.06 1.90*** Ref Ref Ref 1.40** 1.03 1.36 1.68*** 1.08 1.10 0.82 0.57** Ref 1.54** Ref Ref Ref Ref Ref 1.21 1.38 Ref 1.19 1.84*** 1.22 1.03 Ref 0.92 Ref 1.35*** 1.70*** 1.25 0.84* Ref 1.29** 0.71* 0.79** Ref 1.37** Ref 0.61** Ref Ref 0.93 Ref 2.89*** 33.78*** 0.92 1.11 Ref 0.73* 1.01 1.25 1.00 1.74*** 2.03*** 1.50* 1.19 0.9 Ref 0.72 Ref 0.84 0.70* 1.10 1.08 Ref 2.07*** 1.81* 0.84 Ref 0.44* Ref 1.04 0.91 0.82 0.94 Ref 1.57* 0.98 0.64 Ref 0.37*** Ref 1.06 1.18 1.00 1.00 Ref

Sport, recreation, hobby

Employment status

Employed full-time (ref)

Ref

Employed part-time

1.16

Not employed

0.93

Provide care

No (ref)

Ref

Yes

1.15

Background variables

Highest education level

Bachelor degree?

0.88

Diploma

0.99

Vocational qualification

0.91

Completed secondary (ref)

Ref

Incomplete secondary or lower

0.75*

Importance of religion

Not at all important (ref)

Ref

Somewhat important

1.10

Very important/Important

0.71***

Length of time lived at current home

0–1 years

0.72

2–5 years

0.71***

E. Gray et al.

6? years (ref)

Ref

Table 2 continued Welfare, community and health Education, training, and youth dev. Religious Environment, animal welfare Business, professional, union Arts, culture

Sport, recreation, hobby

Country of birth Ref 1.16 0.64** 3,073 -1,567.7 \0.001 \0.001 \0.001 \0.001 -1,255.6 -716.7 -718.7 3,073 3,073 3,073 0.64** 0.95 0.64 0.98 3,073 -598.0 \0.001 1.11 1.59** 1.07 1.35 Ref Ref Ref Ref Ref 1.53* 0.88 3,073 -595.7 \0.001

Australia (ref)

Ref

English-speaking country

0.99

Non-English speaking country

0.44***

Number of observations

3,073

Log likelihood

-1,423.5

Participation in different types of volunteering

Prob [ chi2

\0.001

*p\0.10; ** p\0.05; *** p\0.01

391

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E. Gray et al.

There are no clear patterns of participation in volunteering for environment/ animal welfare organizations by life course stage. Apart from relationship status, having a school-aged child is associated with a lower likelihood of this volunteering, while providing care to an ill or disabled person is associated with a higher likelihood. Volunteering for business, professional and union organizations is more likely for males, and those who are in older adulthood. This type of volunteering is significantly more likely among those aged over 45 compared to the reference category aged 35–44 and is also associated with higher levels of education. Volunteering with arts and culture groups is also more likely among older adults, particularly those aged 55–64. Table 3 shows the results of the second stage of the multivariate analysis, focusing on the life transitions that are associated with volunteering for (a) sport/ recreation/hobby, (b) welfare/community/health and (c) education/training and youth development, by two major age groups aged 25–54 and 55–64. These results show that there are different transitions which affect volunteering for those in middle adulthood and those approaching retirement age. First, for those in middle age, being in the same relationship was associated with participation in both sport/ recreation/hobby and welfare/community/health organizations. Having a child between waves is associated with a decline in participation in sport/recreation/ hobby groups, and those who changed employment or were not employed at all were more likely to participate in education/training/youth development than those employed in both waves. For those aged 55–64, those who were not employed in both waves, or who moved from employment to not being employed were more likely to participate in welfare/community/health groups. This is the most common group volunteered for in this age group, and this transition analysis shows that retirement, or moving out of employment, is associated with volunteering for these types of organization.

Conclusion Volunteers are a heterogeneous group of people who give their time to work with a wide range of organizations. While previous studies have looked at the relationship between life course stage and overall volunteering rates (Sundeen 1990), much less is known about the relationship between life course stage and the types of organization for which people volunteer. Most research on volunteering simply looks at the propensity to volunteer considering individual resources and characteristics. We extend the scope of quantitative research on volunteering by adding ‘where’ people volunteer. In using a life cycle perspective to examine volunteering, we considered life course events in the three dominant life cycle stages: young, middle and later adulthood. As discussed, these life stages are characterized by events which may act as motivators or barriers to participation in volunteering. They are also associated with where people volunteer. Young adulthood is a time when multiple transitions are made such as leaving school, leaving home, starting work, starting a relationship

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Table 3 Logistic regression of volunteering for specific types of organization by age (odds ratios) 55–64 Welfare, community and health Education, training, youth dev. Sport, recreation, hobby Welfare, community and health Education, training, youth dev.

25–54

Sport, recreation, hobby

Sex Ref 1.25 1.38 0.59 0.98 Ref Ref Ref Ref 1.51

Male (ref)

Ref

Female

0.53***

Life course variables Ref 0.36** 0.8 Ref 1.61 Ref 0.65* Ref 0.81 Ref 1.09 1.10 0.95 Ref 0.64 Ref 2.05* 2.11** 2.06* Ref 0.70 n/a 1.55 Ref 2.18** n/a 2.16* Ref 0.72 n/a 2.71*** n/a n/a n/a Ref 1.43 n/a n/a n/a Ref n/a 1.01 0.73 0.55 0.69 Ref Ref Ref 1.00 0.76 n/a Ref 0.66 1.15 n/a

Relationship change (Wave 3–Wave 4)

Participation in different types of volunteering

Same relationship both waves (ref)

Ref

Single both waves

0.31**

Relationship transition

0.45***

Has a pre-school aged child

No (ref)

Ref

Yes

1.17

Has a school aged child

No (ref)

Ref

Yes

1.99***

Had a child between Wave 3 and Wave 4

No (ref)

Ref

Yes

0.46*

Employment change (Wave 3–Wave 4)

Employed both waves (ref)a

Ref

Not employed either wave

1.14

Not employed W3, employed W4

1.40

393

123

Employed W3, not employed W4

1.46

1.77

394

Table 3 continued 55–64 Welfare, community and health Education, training, youth dev. Sport, recreation, hobby Welfare, community and health Education, training, youth dev.

123
Ref 0.64* 0.87 1.89 0.68 Ref Ref Ref Ref 0.93 2.85*** 1.86 1.70 Ref 2.05* 2.68*** 1.73** Ref 0.81 Ref Ref 1.2 0.83 0.48*** Ref Ref 0.59 0.54 Ref 0.99 1.43 1.54 Ref Ref 1.38 1.68 4.03*** Ref 1.54 Ref Ref 0.56 2.08 2.48** 0.89 4.13*** 2.94 4.33*** 1.55 2.52* 1.00 0.96 Ref 0.60 1.67 1.78 Ref 1.14 Ref Ref 1.21 1.93 2.62 2.56 1.64 Ref 0.36 1.53 2.93** Ref 0.79 Ref Ref 0.8 0.26

25–54

Sport, recreation, hobby

Provide care

Yes (ref)

Ref

No

0.93

Background variables

Highest education level

Bachelor degree?

0.95

Diploma

1.10

Vocational qualification

1.19

Completed secondary (ref)

Ref

Incomplete secondary or lower

0.94

Importance of religion

Very important/Important

0.63*

Somewhat important

1.18

Not at all important (ref)

Ref

Length of time lived at current home

0–5 years

0.52***

6? years (ref)

Ref

Country of birth

Australia (ref)

Ref

English-speaking country

0.97

E. Gray et al.

Other

0.45

Table 3 continued 55–64 Welfare, community and health Education, training, youth dev. 641 -273.07 \0.001 0.07 0.02 -113.84 -150.72 253 253 Sport, recreation, hobby Welfare, community and health 641 -327.46 \0.001 Education, training, youth dev. 253 -98.73 0.08

25–54

Sport, recreation, hobby

Number of observations

641

Log likelihood

-366.34

Prob [ chi2

\0.001

* p \ 0.10; ** p \ 0.05; *** p \ 0.01

Participation in different types of volunteering

a

For age group 55–64, this category also includes 8 cases that were not employed in Wave 3 but were employed in Wave 4

395

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E. Gray et al.

or a family, but it is also a time in life when people are more likely to participate in sport and recreation. The results show that 18–24 year olds are as likely to volunteer with sport/recreation/hobby organizations as those aged 35–44 once we control for variables such as presence and age of children, but those aged 25–34 are less likely to participate. Those aged 25–34 are more likely to volunteer with education/ training/youth development. These patterns clearly demonstrate changing priorities, from themselves to their children, with changing life course stages. In middle adulthood, the presence of children is clearly solidified as a major influence on volunteering behaviour. Having school-age children is shown to be associated with a greater likelihood of volunteering in school-related and sport/ recreation/hobby organizations. While we expected that having a pre-school aged child would be associated with less involvement, the multivariate results showed that this applied only to volunteering in sport/recreation/hobby and religious organizations. This suggests that on balance, having a pre-school aged child is not a barrier to most types of volunteering. Later adulthood is associated with increased participation in volunteering with welfare/community/health organizations, business, professional and union groups, and arts and culture organizations, but reduced likelihood of volunteering with sports, recreation and hobby groups. According to life course theory, the importance of significant others is clearly associated with volunteering. People who have partners who volunteer are much more likely to volunteer themselves, and this is confirmed in the data analysis for most types of volunteering except for business-related and arts/culture organizations. The paper also shows that people with caring responsibilities are not significantly less likely to volunteer, but that being a carer is associated with greater propensity to volunteer with groups and organizations related to community and health, environment and animal welfare and business and professional interests. It is possible that volunteering with these groups is related to the individual’s caring responsibilities. This analysis also shows differences by sex, education and birthplace in the type of volunteering. Men are more likely to volunteer in sport and business organizations, while women are more likely to volunteer for welfare, health and education organizations. Those who have a university education are more likely to volunteer with welfare/community/health, education/training/youth, religious, environment/animal welfare, and business-related organizations. Those from nonEnglish-speaking backgrounds are less likely to volunteer with sport/recreation/ hobby, welfare/community/health, and education/training/youth organizations. These findings contribute to our understanding of the types of civic participation in which people engage at different life course stages. Research often focuses on the work/family sphere, but fails to include other activities that individuals engage in. The life course perspective used in this paper to examine participation in different types of volunteering shows that the groups and organizations for which people volunteer are often related to both their family and work responsibilities; situations that change over the life course. This is a significant finding in relation to understanding people’s motivations for volunteering and supports the argument put forward by McDonald and Warburton (2001) of the importance of examining the

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397

contextual factors in understanding why people volunteer. While work and family responsibilities can affect the time people have to volunteer, the findings of this study indicate that they can also provide opportunities for people to volunteer with particular types of groups and organizations. The life course perspective is a particularly useful framework for examining people’s involvement in different types of volunteering because it shows how people’s life circumstances can affect their participation in different types of volunteering either as motivating or inhibiting factors. It also adds to the discourse on the availability of people’s time and personal resources as factors motivating volunteering over the life course (see Warburton et al. 1998). A better understanding of these issues and relationships is also potentially helpful to governments and non-profit groups and organizations in formulating strategies to attract younger and older adults to volunteer.
Acknowledgments The NLC survey is funded by the Australian Research Council (A7990570, DP0208305, DP0663459, DP0987834).

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