Individual Social Capital and Health-Related Quality of Life among Older Rural Chinese
Xiaojie Suna1, Kun Liua1, Martin Webbera2, Lizheng Shia3 c1
a1Centre for Health Management and Policy of Shandong University (key Lab of Health Economics and Policy, National Health and Planning Commission), Jinan, China.
a2International Centre for Mental Health Social Research, Department of Social Policy and Social Work, University of York, UK
a3 Department of Global Health Systems and Development, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, USA
Acknowledgements
This study was funded by the National Nature Science Foundation of China (NSFC #71103112). The funder had no role in the design of the study, the analysis and interpretation of data, or writing of the study.We wish to particularly acknowledge the support of Prof. Chongqi Jia, Dr. Hui Li, Mr. Xiaokang Ji and other participants from Shandong University during the field survey. All named authors meet the criteria for authorship. The authors declare no conflict of interest.
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c1: 1440 Canal Street, Suite 1900, New Orleans, LA 70112, United States of America
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ABSTRACT
No study based on the Resource Generator has explored the association between individual social capital and health-related quality of lifeamong older adults. This study aims to evaluate the validity and reliability of the adapted Resource Generator-China, and examine the association between individual social capital measured by theResource Generator-China and health-related quality of life of older rural-dwelling Chinese people. A field survey including 975 rural-dwellingpeople aged between 60-75 years was conducted in three counties of Shandong Province of China in 2013. Quality of life was measured by the Chineseversion of36-Item Short Form Health Survey:scores of Physical Component Summary and Mental ComponentSummary.Cumulative scale analyses were performed to analyze the homogeneity and reliability of the Resource Generator-China.We constructed generalized linear models by gender to examine the associations of social capital withhealth-related quality of life. Our findings suggest that the adapted instrument for older rural-dwelling Chinese people can be a reliable andvalid measure of access to individual social capital.There were positiveassociations betweenindividual social capital (total scores and subscale scores) and health-related quality of life.Individual social capitalhad a strongerassociationwith mental health among women than men. Future studies should be improved through a longitudinal design with a larger and randomized sample covering large geographical rural areas in China.
KEY WORDS
social capital; quality of life; older people; rural; China
Introduction
In 2013 there were202 million adults of 60 years and aboveliving in China(Wu and Dang 2013).Population ageing in rural areas has been more pronounced than in urban areas (Caiet al. 2012). China is experiencing a demographic transition with anincrease in rural-to-urban migration, particularlyof young people. This has caused dramatic changes in ruralpopulation pyramids and has led toa greater number of older people living alone in rural areas without younger generations to provide late-life care and support.
The social resources embedded in traditional rural social networks play an important rolein the life and health of older people living in rural areas in China(He 2002, Wei 2009). Common problems faced by this group includelabour burdens;economic difficulties; lack of care and support; strong feelings of lonelinessbecause of isolation caused farming and looking after grandchildren;insufficientpension support; and migration of adult children.
A growing body of literature has demonstrated that higher social capital is associated with improved health(Elgaret al. 2011, Kawachiet al. 1997, Lomas 1998, Rocco, Fumagalli and Suhrcke 2014, Whitehead and Diderichsen 2001).Social capital is defined in many ways, but there are two broad approaches. From a communitarian perspective, Putnam defined social capital as “features of social organization, such as trust, norms, and networksthat can improve the efficiency of society by facilitating coordinated actions”(Putnam 1993:167). Another approach isthesocial network perspective of individual social capital (ISC) which, arguably, originated in the writing ofBourdieu. He regarded social capital as "the aggregate of the actual or potential resources which are linked to possession of a durable network"(Bourdieu 1986:248).Similarly, Lin definedsocial capital as“resources embedded in a social structure that are accessed and/ormobilized in purposive actions”(Lin 2001:29). Based on the social network perspective, three main measurement instrumentsfor ISC have been described andapplied in public health research: Name Generator(NG)(Marsden 1987), Position Generator(PG)(Lin and Dumin 1986), and Resource Generator(RG)(Van Der Gaag and Snijders 2005).
The RG method combines the economy of the PG with the content validityof the NG method, because of its vivid measurement ofsocial resources(Webber and Huxley 2007).However, as social resources are cultureand context dependent, different versions of theRG need to be validated for differentpopulations whichmay produce some incomparabilityproblems(Van Der Gaag and Snijders 2005). Before the Resource Generator-UK (RG-UK) was created, resource generatorshad been used in the Netherlands, Canada, Bolivia and Belarussia(Webber and Huxley 2007).The development of the RG-UKinvolved a thoroughcontent validation process, testingof its reliabilityand validity, andan examinationof its internal scales(Webber and Huxley 2007).The sub-domains of the RG-UK are of particular relevancefor health research as they can be used to test hypotheses aboutconnections between access to social resources andhealth status with more precision than the PG, which measures access to occupational prestige(Van der Gaag, Snijders and Flap 2008).
ISC, as measured by the RG-UK, hasan inverserelationship with common mental disorder(Webber and Huxley 2007). Another recent study based on RG-Japan found that ISC was related to improved self-rated health(SRH)(Kobayashiet al. 2013).Although RG-UK and RG-Japan haveboth been used in the generalpopulation, none of the existing RG studies have focusedspecifically on older adults, and noneof the existing RG scales have fully considered the differences between rural and urban residents, and between older adults and others.
The association of social capital with health outcomesinolder adults has been explored in a number of studies. Ichida et al.(2009)found that social capital mediated the relationship between income inequality and health among older adultsfrom 25 Japanese communities. Another Japanese study showed that bonding and bridging social capital had beneficial effects on the health of older Japanese(Murayamaet al. 2013). A recent review of11studies exploringthe relationship between social capital and mental well-being in older peoplefoundpositive associations between components of social capital and aspects of mental well-being(Nyqvistet al. 2013). A Finnish study found that individual-level social participation and trust had a positive association with SRH(Nyqvist, Nygard and Steenbeek 2014). In terms of health-related quality of life (HRQOL), measured by the quality of life (QoL) inventory of the World Health Organization, institutional social capital was shown to be significantly more important for health of older people than for younger people(Muckenhuber, Stronegger and Freidl 2013).Nilsson et al. (2006) found that social capital at the individual level was associated with QoL of older people in rural Bangladesh(Nilsson, Rana and Kabir 2006).A study in USA identified the protective effects of state-level social capital on individual HRQOL(Kim and Kawachi 2007).However, no study based on the RG has explored the association between ISC and HRQOL among older adults, although some scholars have used RG among other population groups(Dutt and Webber 2010, Kobayashi, Kawachi, Iwase, Suzuki and Takao 2013, Webberet al. 2014, Webber, Huxley and Harris 2011). These studiesanalyzedcorrelations of ISC with health indicators such as presence of a common mental disorder, self-rated health measured by a single item“How would you describe your overallstate of health”, and the Hospital Anxiety and Depression scale(Zigmond and Snaith 1983).
In the context of Chinese society, ‘investments’ in social capital to develop and maintain social networks may provide individuals with access to resources and supports.Lin’ssocial capital theory has featured in sociology research in China(Zhang 2011a, Zhang 2011b),but only the NG or PG has been used to measure ISC in China (Bian 2004, Ruanet al. 1990). A good RG tool based on the Chinese context is needed to capture access to and mobilization of socialresources in China.Furthermore, the majority of studies on associations between social capital and health of olderrural Chinese people have been based on Putnam’s theory,and have focused on mental health(Wanget al. 2013). The populations of‘left-behind’ and ‘empty-nested’older rural people are growing and pose a great challenge for China as tohow to mobilize comprehensive social resources to promote their QoL.
Kobayashi et al. observeda differential patternby genderin the sub-domains of the RG-Japan scale, and they argued thatit is important to examine gender difference in theeffects of social capital as measured using the RG(Kobayashi, Kawachi, Iwase, Suzuki and Takao 2013).A study in Sweden also foundgender differencesin the associations between social capital and SRH due to cultural expectations influencing the behaviour of men and women (Erikssonet al. 2011). Therefore, the main aim of this study is to examine the associations of ISC measured by the adaptedRG-Chinascale withHRQOL of olderrural Chinese by gender.
Methods
Study site and sampling method of participants
This study was based on the health and social capital survey of rural-dwelling adults aged 60-75 years in Shandong Province of China in April and May of 2013. Shandong provinceis located in the country’s eastern coastal area and is one of China’s more economically developed regions.Three counties (Junan, Liangshan, Pingyin) from different geographic areas, representing different social economic status, were selected as study sites. Junan, located in the southeast of Shandong, had a population of 822,415, and the per capita GDP was CNY 27,963 ($US4448.81) in 2012. Liangshan, located in the west of Shandong, had a population of 776,299, and the per capita GDP was CNY 26,292 ($US 4,182.96) in 2012.Pingyin, located in the middle of Shandong, had a population of 370,900, and the per capita GDP was CNY 60498 ($US9, 625.04) in 2012. In each county one town was selected which closelyrepresented the economic development, geography and social culture of the whole county. In each of these towns four villages were selected at random. Adults aged 60-75 years in each village, who were at home during the survey, were invited to participate. If there were two or more adults aged 60-75 in one family, one was selected at random to participate in the study.A total of 975 older peopleproviding full data, including the RG-China items, were included in the analysis.
Measures
The Resource GeneratorNetherlands (RG-NL) was the first resource generator scale and included 17 items in four different subscales (Prestige and education related social capital;Political and financial skills social capital;Personal skills social capital; and Personal support social capital)(Van Der Gaag and Snijders 2005).Later versions, including the RG-UKscale, were based on the RG-NL(Webber and Huxley 2007). However, the RG-UKscalewas the first tobe created using a thoroughcontent validation process and to be fully tested for its reliabilityand validity using a non-parametric item response theory method (Webber and Huxley 2007)
To measure social capital for older rural-dwelling adults in China, we adaptedthe RG-UK scale to create the RG-Chinascale.The RG-UK scale was divided intofour empirically-defined internal sub-scales: domestic resources;expert advice; personal skills; and problem solving resources.
To createthe RG-China for rural-dwellingolder adults, a research team member translated the RG-UK into Chinese. This was then back- translated into English by another non-team member. The back-translated RG-UK was compared with the original RG-UK by the whole research team to examine the accuracy of the translation. No major differences between the two editions were found, so only one-round back translation was done.
Secondly, the research team reviewed the RG-UK items and agreed that some items were not suitable for rural-dwelling olderadults in China (see table 1). Therefore, the team developed a new RGscale appropriate foruse in rural China which drew on Chinese social resource and social support tools.Following the RG-UKsubscale classifications, and influenced by aliterature review(He 2002) and focus group discussions, we designed a 30-item RG-China scale, and responses to individual items weredichotomized (0=No, 1=Yes).
Thirdly, nineexperts whose fields included social medicine, health policy, epidemiology and social security,and three local rural health officials, were consulted about the suitability of the 30-item RG-China scale. This consultation led to some items being discarded and new ones being included. A final 29-item RG-China scale was then produced.
Finally, the 29-item RG-China scale was tested in a pilot survey involving 27 rural-dwellingolder adults.A 26-item scale (domestic resources (eight items);expert advice (six items); personal skills (six items); and problem solving resources (six items)) was created on the basis of the findings of this pilot. Compared with the original RG-UK scale, nine items were retained in the new scale and 17 new items were added (see table 1).However, one item in the subscale of problem solving resources (lend you a large amount of money) was subsequently deleted according to preliminaryhomogeneity test results (cut off value of 0.3). Therefore,the final RG-China scaleincluded 25 items.Wecalculated scores for the total scale and each of the subscales.
< Insert Table 1 about here >
We assessed the convergent validity of the RG-China against a PGthat was developed for the purpose of thisstudy. The PG measures access to occupational prestige, a construct similar to social resources accessible through social networks. A similar validity test was used in the development and validation of the RG-UK(Webber and Huxley 2007). The set of 40 PG items suitable for older rural-dwelling Chinesepeople wasbased on the occupation classifications and prestige valuations in earlier research in China(Li 2005). The general question for the PG was whether the respondent‘knew anyone in each of these occupations’. Five deductive PG measures were used based on existing studies(Burt 1992, Campbell, Marsden and Hurlbert 1986, Erickson 1996, Erickson 2003, Lin 1999, Lin 2001). Highest accessed prestige is a regularly used social capital measure referring to specific socialresource quality, and is based on the hypothesis that positive social capital resultsfrom accessing network members with high prestige(Lin 2001). Range in accessedprestige is calculated as the difference between highest and lowest accessed prestige,while number of different positions accessed is the total number of occupations inwhich a respondent knows anyone.The average accessed prestige iscalculated as the mean of the prestige of all occupations in which the respondent knows anyone. Total accessed prestige is a calculated as the cumulative prestige ofall accessed occupations.
Our outcome measure was HRQOLmeasured bythe Chinese-version of 36-Item Short Form Health Survey(SF-36).The Chinese-version of SF-36 was translated fromSF-36 Standard UK Version 1.0 by the Institute of Social Medicine and General Practice ofZhejiang University, China(Li, Wang and Shen 2003).This version of SF-36 has previously been used insurveys to assess the QoLof both the general population and people with specific chronic diseases(Liang, Xue and Jing 2005, Wanget al. 2008).The Chinese-version of SF-36 yields eight scale profilesmeasuring eight domains of QoLtargeting physicalfunctioning, role-physical, role-emotion,bodily pain, general health, vitality, social functioning,and mental health. The eightSF-36 domains hypothetically formed two categories:Physical Component Summary (PCS) and Mental ComponentSummary (MCS), respectively.The scores of PCS and MCS were obtained using thestandard scoring algorithms(Lamet al. 2005).
We included the following variables as potential confounders inthe generalized linear regression models:age (continuous), gender, education (illiterate/primary school/junior secondary school/high school and above), occupation before 60 years old (farmer vs. non-farmers), annual family income per capita (continuous), living arrangement (living alone/living with spouse/living with spouse and others/living with others), county (Junan/Liangshan/Pingyin) and presence/absence of chronic illness.
Statistical analysis
Since RG data are typically of an ordinalnature, factor-analytic models such as Principal Components Analysis(designed for use with normally distributed data of at least 5 categories) aregenerally not suitable to accomplish such dimensional reductions. Instead,models from Item Response Theory are more appropriate(Van der Linden and Hambleton 1997). To analyze the homogeneity and reliability of RG-China scale, cumulative scale analyses were performed usingMSP5 for Windows (Molenaar and Sijtsma 2000). Mokken scales use Loevinger’s coefficient of homogeneity at the item (Hi) and scale (H) levels to test whether the number of departures from a strictly hierarchical response pattern is low enough that persons and items can be consistently ordered(Molenaar and Sijtsma 2000).Loevinger’s H-coefficients (Loevinger 1947)was used to express the fit of specific items within ascale and for the homogeneity of the scale as awhole. Uncorrelated items produced values of H=0,whereas perfectly homogenous scales producedvalues of H=1. Conventionally, scales withH≥0.3 are useful, H≥0.4 are medium strong andH≥0.5 are strong scales (Mokken 1997).We eliminateditems if their item homogeneity H coefficients (Hi) fell below a setvalue, conventionally Hi=0.3 (Mokken 1997). Further, areliability coefficientρ was calculated for the total scale and each subscale.Values above 0.6 are conventionally taken asindications of sufficient reliability (Molenaar and Sijtsma 2000).
Pearson correlation analysis was used to analyze the correlation relationships between different RG subscales, and between RG and PG measures. Following Kobayashi,et al.’s analytical approach to separate the analysis by gender(Kobayashi, Kawachi, Iwase, Suzuki and Takao 2013), we constructed four generalized linear regression models by gender to examine the associations of social capital status based on RG scale with HRQOL (PCS and MCS) among older rural-dwelling Chinese people, after controlling for other confounders. In model one and model two, we introduced RG total scale score (the models based on continuous and categorical total RG were both tried); in model three and model four, we introduced four RG subscale scores. In this study, p values of less than 0.05 (two-sidedtest) were considered statistically significant.These analyseswere performed using STATA 12.0(StataCorp 2011).