513623 research-article2013
HPQ0010.1177/1359105313513623Journal of Health PsychologyDageid and Grønlie
Article
The associations between resilience, social capital and self-rated health among HIV-positive South Africans
Journal of Health Psychology 0(0) 1–11 © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1359105313513623 hpq.sagepub.com
Wenche Dageid1 and Anette A Grønlie1,2
Abstract This study examined the relationship between resilience, social capital and self-rated health among 263 HIV-positive South Africans living in poverty, using questionnaires. Self-rated good health was predicted by younger age, trust in community-based organizations and having contacts of different religions. The findings highlight the importance of community-based networks and resources for care and support for persons living with HIV/AIDS in poor, rural areas. Furthermore, resilience, which also related positively to education and income, contributed positively to self-rated health, drawing attention to the interplay between resources at individual and community levels.
Keywords HIV, resilience, self-rated health, social capital, South Africa
Introduction It is widely accepted that economic and social factors, in particular systemic inequality, influence health negatively (Marmot et al., 2008). South Africa is characterized as a middleincome country, yet is marked by very high levels of inequality (Coovadia et al., 2009). This inequality affects the majority of its population, who still live in poverty-stricken areas with inadequate material resources and poor service delivery (Møller, 2007). HIV/AIDS is another major hardship for many South Africans, disproportionately affecting already disadvantaged communities (Williams et al., 2007). Psychological factors such as resilience have been associated with better health outcomes (Smith, 2006; Yeung et al., 2012).
Despite the focus on societal factors and resilience in explaining health, information is still scarce with regards to the interplay between demographic, psychological and social factors in explaining health in particular contexts. HIVpositive persons are faced with a range of physical, psychological and social challenges that 1University
of Oslo, Norway Norwegian Center for Child Behavioral Development, Norway
2The
Corresponding Author: Wenche Dageid, Department of Psychology, University of Oslo, P.O. Box 1094, Blindern, 0317 Oslo, Norway. Email: [email protected]; [email protected]
Downloaded from hpq.sagepub.com at UNIV OF PENNSYLVANIA on October 27, 2015
2
Journal of Health Psychology 0(0)
make them particularly vulnerable to negative health outcomes (Webel et al., 2012). The purpose of this article is to examine the influence of demographic background variables, resilience and social capital on self-rated health among South African HIV-positive women and men living in a context of adversity. The relations between demographic factors and self-rated health have been extensively studied worldwide. Higher income (Giordano and Lindström, 2010), higher levels of education (Dahl and Malmberg-Heimonen, 2010), higher subjective social status (Camelo et al., 2013), younger age (Yiengprugsawan et al., 2011), and being male (Yamaoka, 2008) have been found to influence self-rated health positively. A study conducted in South Africa found that poor self-rated health was related to unemployment, poor education, and advanced age (Cramm and Nieboer, 2011). A growing body of research documents the importance of social capital in regards to selfrated health (Giordano and Lindström, 2010; Webel et al., 2012). Social capital can be defined as resources that are embedded in and can be accessed through social networks (Bourdieu, 1986; Putnam, 1993). In a systematic review of studies on social capital and health, Kawachi et al. (2008) found consistent positive associations between trust and self-rated health. Another recent meta-analysis found that social capital increased the odds of reporting good health by 27 per cent (Gilbert et al., 2013), with the strongest effects reported for reciprocity (39%) and trust (32%). Furthermore, good selfrated health was more strongly associated with bonding social capital than with bridging and linking social capital (Gilbert et al., 2013). Stronger associations between social capital and self-rated health were found in countries with higher degrees of economic inequality than in more egalitarian countries (Islam et al., 2006). South Africa is one of the least economically egalitarian countries in the world (Bhorat et al., 2009), so we would expect social capital to influence levels of self-rated health in our study. Low social support has been significantly related to poor self-rated health (Yiengprugsawan et al.,
2011). Networks are crucial resources to get by in poor areas (Ferlander, 2007). Home-based care groups consisting of lay community health workers are of particular importance to persons living with HIV/AIDS (PLWHAs) in poor communities in South Africa (Schneider and Lehmann, 2010). While social capital is believed to be a quality of networks and socially embedded norms and values, resilience represents a more psychological and personally embedded quality. Following a review of more than 270 research articles, Windle (2011) defined resilience as The process of negotiating, managing and adapting to significant sources of stress or trauma. Assets and resources within the individual, their life and environment facilitate this capacity for adaptation and ‘bouncing back’ in the face of adversity. Across the life course, the experience of resilience will vary. (p. 163)
Resilience has been associated with a range of health outcomes (e.g. Friborg et al., 2006a; Pinkerton and Dolan, 2007; Smith, 2006). To our knowledge, no previous study has explored the relations of resilience, social capital, and self-rated health in HIV-positive individuals in developing countries. Based on previous research, we assumed that income, education and age, and social capital, in particular trust, would be associated with self-rated health. We also assumed that higher scores on resilience would be associated with better selfrated health.
Method Participants and procedure The data used for this study are derived from a survey including 263 HIV-positive men (16%) and women (84%) in the province of KwaZuluNatal, South Africa (95% response rate). All were members of local Treatment Action Campaign (TAC) HIV support groups. TAC is a non-governmental organization (NGO) in South Africa with more than 16,000 members in over 260 branches. The organization works to
Downloaded from hpq.sagepub.com at UNIV OF PENNSYLVANIA on October 27, 2015
3
Dageid and Grønlie secure access to treatment, care and support services for PLWHAs as well as working with prevention campaigns. We visited 14 support groups, which were located in townships in KwaZulu-Natal, and recruited the participants during their weekly group meetings. As the participants were mainly isiZulu speaking, the instruments were translated into isiZulu and the data collection was aided by an isiZulu speaking interpreter. The questionnaires were administered on paper; however, as many of the participants had never filled out questionnaires before the interpreter assisted the groups and read aloud all questions and response alternatives. If the questions were perceived to be ambiguous, the participants could address this via the interpreter and researcher, who were available to clarify any questions the participants had throughout each session. Each session lasted approximately 2 hours. Lunch, refreshments, and money for transport to and from the meeting were provided. All participants gave written informed consent to participate in the study. Respondents age’ ranged from 18 to 67 years (M = 35.5 years). They had on average known about their HIV-positive status for 3.9 years (range from 1 month to 15 years). A majority of the participants (74%) were single, 20 per cent were married, while the remaining 6 per cent were widowed, divorced, or separated. A majority of the participants (75%) had completed grade nine, while the remaining 25 per cent had further education (grade 10–12). Only one person had university education. Six out of 10 participants reported no household income, while 26 per cent had a household income of one-999 South African Rand (R) (100 R = 7.7 Euro). The remaining 14 per cent reported a household income of between 1000–6000 R.
Instruments Self-rated health. Self-rated health was measured by the single question ‘In general, how would you rate your health these days?’ with answering options 1 = poor, 2 = fair, 3 = neither good nor poor, 4 = good and 5 = excellent. This
single item has proved a reliable measure of health (Idler and Benyamini, 1997). Resilience. This study used a revised version of The Resilience Scale for Adults (RSA) (Friborg et al., 2006b). Three items were removed from the original scale to improve internal consistency. The scale used for analysis was thus composed of 30 items, which measure five resilience factors: planned future (4 items), perception of self (6 items), family cohesion (6 items), social resources (6 items), social competence (5 items) and structured style (3 items). The Cronbach’s alphas (α) of the subscales were satisfactory, ranging from .52 to .65 (mean inter-item correlations ranged from r = .18 to r = .29) (see Dageid and Grønlie, 2013 for further information). All items were rated on a7-point scale, with two semantically different anchors at each end. The 30 items were added to produce a total resilience score, which showed good internal consistency (α = .82). Scores on the total RSA could range from 30 to 210. Social capital. Our social capital questionnaire was largely based on The World Bank Group’s The Social Capital Assessment Tool (SOCAT) (Grootaert and Van Bastelaer, 2001; Krishna and Shrader, 1999). Structural social capital was measured by number of groups and organizations a person was member in; number of friends; diversity among the contacts a person had (in terms of race, gender, socio-economic status and religion); and collective action (community initiatives directed at the government). Cognitive social capital was measured by the items perceived importance of being member of a group; general trust (‘Would you say people can be trusted or cannot be trusted’); neighbour trust (‘If you had to go away, would you trust your neighbours to look out for your children’?); trust at a bonding level (in partner, friends, and family); trust at a bridging level (in traditional leaders, and HIV-related community-based organizations (CBOs) present in the community); trust at a linking level (in the formal health care system, HIV-related NGOs, government); norms of reciprocity (‘Would you
Downloaded from hpq.sagepub.com at UNIV OF PENNSYLVANIA on October 27, 2015
4
Journal of Health Psychology 0(0)
say that most of the time people try to be helpful, or are they looking out for themselves’), community solidarity (‘How likely that people in this community would help a family who lost someone to AIDS?’), and voices being heard by government (‘To what extent have the government taken into account concerns raised by the community when making decisions?’). Most items were rated on a 5-point scale (5 denoting the most positive answering option) with various statement and response alternatives, and some items were open-ended.
Data analysis Data was analysed with SPSS version 20, using t-tests and partial correlation analysis, followed by binary logistic regression to explore the differences (in terms of odds) of reporting good health based on demographic variables, resilience and social capital. All tests were twotailed (p < .05).
Results Descriptive information and differences between those with poor health and good health The mean score on self-rated health in our sample was 2.59 (standard deviation (SD) = 1.18). Only 6.5 per cent characterized their health as excellent, 14.6 per cent as good, 35.2 per cent as average, 19.2 per cent as fair and 24.5 per cent characterized their health as poor. For the purpose of this article, the variable was dichotomized, with answering options 1, 2 and 3 denoting poor health and given the code 0. Answering options 4 and 5 were given the code 1, which denoted good health. The income variable originally contained six categories, but analysis revealed that the main difference in health was between those who had an income versus those who had none. This variable was therefore dichotomized in the further analysis. Table 1 provides a descriptive oversight of the distribution of scores, as well as differences on
all variables for those who rated their health as poor and good, respectively. To explore the relations and potential problems of co-linearity between all variables in the study, correlations were performed. Apart from the expected high correlations between subscales of the RSA, other correlations (all at p < .001) were low or moderate. The highest correlations were found between trust in family and trust in friends (r = .40), having contacts of different SES and gender (r = .38), having contacts of different religion and different gender (r = .37), household income and total resilience score (r = .34), education and the resilience sub-scale social competence (r = .34), trust in partner and community solidarity (r = .29), having contacts of different religion and different race (r = .26), general trust and total resilience (r = .23), and trust in family and total resilience (r = .23).
Variables predicting self-rated health Entering all variables which significantly distinguished between the groups with poor and good self-rated health into a logistic regression, the following result was produced (see Table 2). The analyses revealed that being of older age was significantly negatively related to good health, while resilience, having contacts of different religious groups and trust in HIV-related CBOs were significantly positively related to good health. The model explained 32.4 per cent (Nagelkerke R2) of the variance in scores on self-rated health. Substituting the total RSA scale for subscales led to non-significant predictive values for resilience. It was therefore decided to use the total RSA score in the regression model. Adding the near significant variables gender, trust in traditional leadership and norms of reciprocity to the model did not change the results significantly.
Discussion This study showed that four variables increased the odds of reporting good health in this
Downloaded from hpq.sagepub.com at UNIV OF PENNSYLVANIA on October 27, 2015
5
Dageid and Grønlie Table 1. Descriptive statistics and differences on background variables, resilience, and social capital for participants reporting poor and good health respectively (n = 263).
Background variables Gender Men Women Age Marital status Single Married/engaged Widowed/divorced/separated Household income No income Income Education completed (years/grade) Months of known HIV status Resilience Total score RSA Planned future Perception of self Family cohesion Social resources Social competence Structured style Social capital Structural social capital Number of membership groups Number of friends Contacts of different (yes) Race Gender Religion SES Collective action Cognitive social capital Importance of group memberships General trust Neighbour trust Bonding trust partner Bonding trust friends Bonding trust family Bridging trust traditional leaders Bridging trust HIV CBOs Linking trust health-care system
Poor self-rated health
Good self-rated health
%
%
Mean (SD)
Mean (SD)
p-value
8.6 (3.2) 53.9 (41.7)
9.7 (2.4) 42.3 (35.7)
.089 .000** .897 .005** .002** .023*
146.0 (28.6)
163.2 (28.0)
.000**
17.8 (8.0) 35.3 (10.3) 28.2 (9.3) 22.1 (6.1) 24.2 (7.5) 16.1 (5.3)
20.8 (8.0) 40.0 (8.9) 32.5 (8.5) 24.0 (5.3) 26.5 (7.2) 18.2 (4.1)
.004** .000** .000** .007** .015* .000**
2.6 (1.2) 9.1 (8.5)
2.7 (3.1) 9.1 (8.8)
.749 .969
2.3 (1.5)
2.5 (1.6)
.038* .533 .002** .131 .261
3.7 (1.3) 3.2 (1.2) 2.9 (1.6) 3.0 (1.7) 3.3 (1.6) 3.3 (1.7) 2.1 (1.4) 2.5 (1.5) 3.7 (1.6)
3.7 (1.2) 3.5 (1.0) 3.5 (1.5) 3.1 (1.6) 3.3 (1.4) 3.5 (1.4) 2.5 (1.4) 3.3 (1.6) 3.5 (1.5)
. 659 .115 .001** .723 .878 .211 .061 .000** .402
31.0 46.1
69.0 53.9 38.4 (9.4)
33.2 (9.1)
43.0 46.2 46.7
57.0 53.8 53.3
51.0 32.7
49.0 67.3
64.4 80.2 58.3 79.6
77.5 76.7 77.0 70.5
(continued)
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Journal of Health Psychology 0(0)
Table 1. (continued)
Poor self-rated health
Good self-rated health
%
%
Mean (SD)
Linking trust HIV NGOs Linking trust government Norms of reciprocity Community solidarity Voices being heard by government
3.5 (1.7) 2.3 (1.5) 2.6 (1.4) 3.2 (1.3) 2.0 (1.2)
Mean (SD) 3.5 (1.7) 2.6 (1.4) 2.9 (01.5) 3.3 (1.3) 2.3 (1.2)
p-value .764 .104 .052 .351 .048*
SD: standard deviation; RSA: Resilience Scale for Adults; SES: socio-economic status; CBO: community-based organization; NGO: non-governmental organization. *p < .05, **p < .01.
Table 2. Logistic regression analyses of variables on health (reference group good health, n = 263).. Variables
B
Age Income (having income) Education Duration knowing HIV status Total score RSA Contacts different race (yes) Contacts different religion (yes) Neighbour trust Bridging trust HIV CBOs Voices being heard by government Constant −2 log likelihood Overall model evaluation
−.089 .139 −.034 −.006 .022 .278 .962 .072 .291 .015 −1.455 166.903
SE
Wald F
OR (95% CI for EXP (B))
.025 .422 .072 .006 .008 .437 .479 .129 .124 .160 1.440
12.192 .109 .221 1.119 8.445 .406 4.025 .315 5.462 .009 1.021
.915 (.870–.962) 1.149 (.503–2.627) .967 (.839–1.114) .994 (.983–1.005) 1.023 (1.007–1.038) 1.321 (.561–3.110) 2.616 (1.022–6.694) 1.075 (.835–1.384) 1.338 (1.048–1.707) 1.015 (.742–1.390)
χ2 42.877
df 10
p .000 .741 .638 .290 .004 .524 .045 .575 .019 .924 p
HPQ0010.1177/1359105313513623Journal of Health PsychologyDageid and Grønlie
Article
The associations between resilience, social capital and self-rated health among HIV-positive South Africans
Journal of Health Psychology 0(0) 1–11 © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1359105313513623 hpq.sagepub.com
Wenche Dageid1 and Anette A Grønlie1,2
Abstract This study examined the relationship between resilience, social capital and self-rated health among 263 HIV-positive South Africans living in poverty, using questionnaires. Self-rated good health was predicted by younger age, trust in community-based organizations and having contacts of different religions. The findings highlight the importance of community-based networks and resources for care and support for persons living with HIV/AIDS in poor, rural areas. Furthermore, resilience, which also related positively to education and income, contributed positively to self-rated health, drawing attention to the interplay between resources at individual and community levels.
Keywords HIV, resilience, self-rated health, social capital, South Africa
Introduction It is widely accepted that economic and social factors, in particular systemic inequality, influence health negatively (Marmot et al., 2008). South Africa is characterized as a middleincome country, yet is marked by very high levels of inequality (Coovadia et al., 2009). This inequality affects the majority of its population, who still live in poverty-stricken areas with inadequate material resources and poor service delivery (Møller, 2007). HIV/AIDS is another major hardship for many South Africans, disproportionately affecting already disadvantaged communities (Williams et al., 2007). Psychological factors such as resilience have been associated with better health outcomes (Smith, 2006; Yeung et al., 2012).
Despite the focus on societal factors and resilience in explaining health, information is still scarce with regards to the interplay between demographic, psychological and social factors in explaining health in particular contexts. HIVpositive persons are faced with a range of physical, psychological and social challenges that 1University
of Oslo, Norway Norwegian Center for Child Behavioral Development, Norway
2The
Corresponding Author: Wenche Dageid, Department of Psychology, University of Oslo, P.O. Box 1094, Blindern, 0317 Oslo, Norway. Email: [email protected]; [email protected]
Downloaded from hpq.sagepub.com at UNIV OF PENNSYLVANIA on October 27, 2015
2
Journal of Health Psychology 0(0)
make them particularly vulnerable to negative health outcomes (Webel et al., 2012). The purpose of this article is to examine the influence of demographic background variables, resilience and social capital on self-rated health among South African HIV-positive women and men living in a context of adversity. The relations between demographic factors and self-rated health have been extensively studied worldwide. Higher income (Giordano and Lindström, 2010), higher levels of education (Dahl and Malmberg-Heimonen, 2010), higher subjective social status (Camelo et al., 2013), younger age (Yiengprugsawan et al., 2011), and being male (Yamaoka, 2008) have been found to influence self-rated health positively. A study conducted in South Africa found that poor self-rated health was related to unemployment, poor education, and advanced age (Cramm and Nieboer, 2011). A growing body of research documents the importance of social capital in regards to selfrated health (Giordano and Lindström, 2010; Webel et al., 2012). Social capital can be defined as resources that are embedded in and can be accessed through social networks (Bourdieu, 1986; Putnam, 1993). In a systematic review of studies on social capital and health, Kawachi et al. (2008) found consistent positive associations between trust and self-rated health. Another recent meta-analysis found that social capital increased the odds of reporting good health by 27 per cent (Gilbert et al., 2013), with the strongest effects reported for reciprocity (39%) and trust (32%). Furthermore, good selfrated health was more strongly associated with bonding social capital than with bridging and linking social capital (Gilbert et al., 2013). Stronger associations between social capital and self-rated health were found in countries with higher degrees of economic inequality than in more egalitarian countries (Islam et al., 2006). South Africa is one of the least economically egalitarian countries in the world (Bhorat et al., 2009), so we would expect social capital to influence levels of self-rated health in our study. Low social support has been significantly related to poor self-rated health (Yiengprugsawan et al.,
2011). Networks are crucial resources to get by in poor areas (Ferlander, 2007). Home-based care groups consisting of lay community health workers are of particular importance to persons living with HIV/AIDS (PLWHAs) in poor communities in South Africa (Schneider and Lehmann, 2010). While social capital is believed to be a quality of networks and socially embedded norms and values, resilience represents a more psychological and personally embedded quality. Following a review of more than 270 research articles, Windle (2011) defined resilience as The process of negotiating, managing and adapting to significant sources of stress or trauma. Assets and resources within the individual, their life and environment facilitate this capacity for adaptation and ‘bouncing back’ in the face of adversity. Across the life course, the experience of resilience will vary. (p. 163)
Resilience has been associated with a range of health outcomes (e.g. Friborg et al., 2006a; Pinkerton and Dolan, 2007; Smith, 2006). To our knowledge, no previous study has explored the relations of resilience, social capital, and self-rated health in HIV-positive individuals in developing countries. Based on previous research, we assumed that income, education and age, and social capital, in particular trust, would be associated with self-rated health. We also assumed that higher scores on resilience would be associated with better selfrated health.
Method Participants and procedure The data used for this study are derived from a survey including 263 HIV-positive men (16%) and women (84%) in the province of KwaZuluNatal, South Africa (95% response rate). All were members of local Treatment Action Campaign (TAC) HIV support groups. TAC is a non-governmental organization (NGO) in South Africa with more than 16,000 members in over 260 branches. The organization works to
Downloaded from hpq.sagepub.com at UNIV OF PENNSYLVANIA on October 27, 2015
3
Dageid and Grønlie secure access to treatment, care and support services for PLWHAs as well as working with prevention campaigns. We visited 14 support groups, which were located in townships in KwaZulu-Natal, and recruited the participants during their weekly group meetings. As the participants were mainly isiZulu speaking, the instruments were translated into isiZulu and the data collection was aided by an isiZulu speaking interpreter. The questionnaires were administered on paper; however, as many of the participants had never filled out questionnaires before the interpreter assisted the groups and read aloud all questions and response alternatives. If the questions were perceived to be ambiguous, the participants could address this via the interpreter and researcher, who were available to clarify any questions the participants had throughout each session. Each session lasted approximately 2 hours. Lunch, refreshments, and money for transport to and from the meeting were provided. All participants gave written informed consent to participate in the study. Respondents age’ ranged from 18 to 67 years (M = 35.5 years). They had on average known about their HIV-positive status for 3.9 years (range from 1 month to 15 years). A majority of the participants (74%) were single, 20 per cent were married, while the remaining 6 per cent were widowed, divorced, or separated. A majority of the participants (75%) had completed grade nine, while the remaining 25 per cent had further education (grade 10–12). Only one person had university education. Six out of 10 participants reported no household income, while 26 per cent had a household income of one-999 South African Rand (R) (100 R = 7.7 Euro). The remaining 14 per cent reported a household income of between 1000–6000 R.
Instruments Self-rated health. Self-rated health was measured by the single question ‘In general, how would you rate your health these days?’ with answering options 1 = poor, 2 = fair, 3 = neither good nor poor, 4 = good and 5 = excellent. This
single item has proved a reliable measure of health (Idler and Benyamini, 1997). Resilience. This study used a revised version of The Resilience Scale for Adults (RSA) (Friborg et al., 2006b). Three items were removed from the original scale to improve internal consistency. The scale used for analysis was thus composed of 30 items, which measure five resilience factors: planned future (4 items), perception of self (6 items), family cohesion (6 items), social resources (6 items), social competence (5 items) and structured style (3 items). The Cronbach’s alphas (α) of the subscales were satisfactory, ranging from .52 to .65 (mean inter-item correlations ranged from r = .18 to r = .29) (see Dageid and Grønlie, 2013 for further information). All items were rated on a7-point scale, with two semantically different anchors at each end. The 30 items were added to produce a total resilience score, which showed good internal consistency (α = .82). Scores on the total RSA could range from 30 to 210. Social capital. Our social capital questionnaire was largely based on The World Bank Group’s The Social Capital Assessment Tool (SOCAT) (Grootaert and Van Bastelaer, 2001; Krishna and Shrader, 1999). Structural social capital was measured by number of groups and organizations a person was member in; number of friends; diversity among the contacts a person had (in terms of race, gender, socio-economic status and religion); and collective action (community initiatives directed at the government). Cognitive social capital was measured by the items perceived importance of being member of a group; general trust (‘Would you say people can be trusted or cannot be trusted’); neighbour trust (‘If you had to go away, would you trust your neighbours to look out for your children’?); trust at a bonding level (in partner, friends, and family); trust at a bridging level (in traditional leaders, and HIV-related community-based organizations (CBOs) present in the community); trust at a linking level (in the formal health care system, HIV-related NGOs, government); norms of reciprocity (‘Would you
Downloaded from hpq.sagepub.com at UNIV OF PENNSYLVANIA on October 27, 2015
4
Journal of Health Psychology 0(0)
say that most of the time people try to be helpful, or are they looking out for themselves’), community solidarity (‘How likely that people in this community would help a family who lost someone to AIDS?’), and voices being heard by government (‘To what extent have the government taken into account concerns raised by the community when making decisions?’). Most items were rated on a 5-point scale (5 denoting the most positive answering option) with various statement and response alternatives, and some items were open-ended.
Data analysis Data was analysed with SPSS version 20, using t-tests and partial correlation analysis, followed by binary logistic regression to explore the differences (in terms of odds) of reporting good health based on demographic variables, resilience and social capital. All tests were twotailed (p < .05).
Results Descriptive information and differences between those with poor health and good health The mean score on self-rated health in our sample was 2.59 (standard deviation (SD) = 1.18). Only 6.5 per cent characterized their health as excellent, 14.6 per cent as good, 35.2 per cent as average, 19.2 per cent as fair and 24.5 per cent characterized their health as poor. For the purpose of this article, the variable was dichotomized, with answering options 1, 2 and 3 denoting poor health and given the code 0. Answering options 4 and 5 were given the code 1, which denoted good health. The income variable originally contained six categories, but analysis revealed that the main difference in health was between those who had an income versus those who had none. This variable was therefore dichotomized in the further analysis. Table 1 provides a descriptive oversight of the distribution of scores, as well as differences on
all variables for those who rated their health as poor and good, respectively. To explore the relations and potential problems of co-linearity between all variables in the study, correlations were performed. Apart from the expected high correlations between subscales of the RSA, other correlations (all at p < .001) were low or moderate. The highest correlations were found between trust in family and trust in friends (r = .40), having contacts of different SES and gender (r = .38), having contacts of different religion and different gender (r = .37), household income and total resilience score (r = .34), education and the resilience sub-scale social competence (r = .34), trust in partner and community solidarity (r = .29), having contacts of different religion and different race (r = .26), general trust and total resilience (r = .23), and trust in family and total resilience (r = .23).
Variables predicting self-rated health Entering all variables which significantly distinguished between the groups with poor and good self-rated health into a logistic regression, the following result was produced (see Table 2). The analyses revealed that being of older age was significantly negatively related to good health, while resilience, having contacts of different religious groups and trust in HIV-related CBOs were significantly positively related to good health. The model explained 32.4 per cent (Nagelkerke R2) of the variance in scores on self-rated health. Substituting the total RSA scale for subscales led to non-significant predictive values for resilience. It was therefore decided to use the total RSA score in the regression model. Adding the near significant variables gender, trust in traditional leadership and norms of reciprocity to the model did not change the results significantly.
Discussion This study showed that four variables increased the odds of reporting good health in this
Downloaded from hpq.sagepub.com at UNIV OF PENNSYLVANIA on October 27, 2015
5
Dageid and Grønlie Table 1. Descriptive statistics and differences on background variables, resilience, and social capital for participants reporting poor and good health respectively (n = 263).
Background variables Gender Men Women Age Marital status Single Married/engaged Widowed/divorced/separated Household income No income Income Education completed (years/grade) Months of known HIV status Resilience Total score RSA Planned future Perception of self Family cohesion Social resources Social competence Structured style Social capital Structural social capital Number of membership groups Number of friends Contacts of different (yes) Race Gender Religion SES Collective action Cognitive social capital Importance of group memberships General trust Neighbour trust Bonding trust partner Bonding trust friends Bonding trust family Bridging trust traditional leaders Bridging trust HIV CBOs Linking trust health-care system
Poor self-rated health
Good self-rated health
%
%
Mean (SD)
Mean (SD)
p-value
8.6 (3.2) 53.9 (41.7)
9.7 (2.4) 42.3 (35.7)
.089 .000** .897 .005** .002** .023*
146.0 (28.6)
163.2 (28.0)
.000**
17.8 (8.0) 35.3 (10.3) 28.2 (9.3) 22.1 (6.1) 24.2 (7.5) 16.1 (5.3)
20.8 (8.0) 40.0 (8.9) 32.5 (8.5) 24.0 (5.3) 26.5 (7.2) 18.2 (4.1)
.004** .000** .000** .007** .015* .000**
2.6 (1.2) 9.1 (8.5)
2.7 (3.1) 9.1 (8.8)
.749 .969
2.3 (1.5)
2.5 (1.6)
.038* .533 .002** .131 .261
3.7 (1.3) 3.2 (1.2) 2.9 (1.6) 3.0 (1.7) 3.3 (1.6) 3.3 (1.7) 2.1 (1.4) 2.5 (1.5) 3.7 (1.6)
3.7 (1.2) 3.5 (1.0) 3.5 (1.5) 3.1 (1.6) 3.3 (1.4) 3.5 (1.4) 2.5 (1.4) 3.3 (1.6) 3.5 (1.5)
. 659 .115 .001** .723 .878 .211 .061 .000** .402
31.0 46.1
69.0 53.9 38.4 (9.4)
33.2 (9.1)
43.0 46.2 46.7
57.0 53.8 53.3
51.0 32.7
49.0 67.3
64.4 80.2 58.3 79.6
77.5 76.7 77.0 70.5
(continued)
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6
Journal of Health Psychology 0(0)
Table 1. (continued)
Poor self-rated health
Good self-rated health
%
%
Mean (SD)
Linking trust HIV NGOs Linking trust government Norms of reciprocity Community solidarity Voices being heard by government
3.5 (1.7) 2.3 (1.5) 2.6 (1.4) 3.2 (1.3) 2.0 (1.2)
Mean (SD) 3.5 (1.7) 2.6 (1.4) 2.9 (01.5) 3.3 (1.3) 2.3 (1.2)
p-value .764 .104 .052 .351 .048*
SD: standard deviation; RSA: Resilience Scale for Adults; SES: socio-economic status; CBO: community-based organization; NGO: non-governmental organization. *p < .05, **p < .01.
Table 2. Logistic regression analyses of variables on health (reference group good health, n = 263).. Variables
B
Age Income (having income) Education Duration knowing HIV status Total score RSA Contacts different race (yes) Contacts different religion (yes) Neighbour trust Bridging trust HIV CBOs Voices being heard by government Constant −2 log likelihood Overall model evaluation
−.089 .139 −.034 −.006 .022 .278 .962 .072 .291 .015 −1.455 166.903
SE
Wald F
OR (95% CI for EXP (B))
.025 .422 .072 .006 .008 .437 .479 .129 .124 .160 1.440
12.192 .109 .221 1.119 8.445 .406 4.025 .315 5.462 .009 1.021
.915 (.870–.962) 1.149 (.503–2.627) .967 (.839–1.114) .994 (.983–1.005) 1.023 (1.007–1.038) 1.321 (.561–3.110) 2.616 (1.022–6.694) 1.075 (.835–1.384) 1.338 (1.048–1.707) 1.015 (.742–1.390)
χ2 42.877
df 10
p .000 .741 .638 .290 .004 .524 .045 .575 .019 .924 p
