Gender differences in relationships between social capital
and individual smoking and drinking behavior in Taiwan
q
Ying-Chih Chuang
*, Kun-Yang Chuang
Graduate Institute of Public Health, Taipei Medical University, Taipei, Taiwan
a r t i c l e
i n f o
Article history:
Available online 28 July 2008 Keywords: Taiwan Neighborhoods Social capital Gender Smoking Drinking
a b s t r a c t
Despite the concept of social capital receiving great attention in the area of health research, few studies have analyzed the differential effects of social capital between genders. This article assesses gender differences in the relationships between social capital and smoking and drinking behavior in Taiwan. Data on individual sociodemographic characteristics, smoking, drinking, and social capital were obtained from the Taiwan Social Change Survey conducted in 1995 and in 2000. The overall response rate was 67%. In total, 3713 women and men aged over 20 years living in 204 neighborhoods were interviewed. Social capital indicators were aggregated at the neighborhood level, and included neighborhood close-ness, political influence, social contact, social trust, and social participation. The data were analyzed with multilevel binomial regression models. Gender differences were found in some aspects of social capital. Stronger effects of social trust on smoking were found for women than for men, whereas stronger effects of neighborhood closeness on drinking were found for women than for men. Social participation was positively associated with drinking in both genders. The findings of this study provide new evidence for the differen-tial effects of social capital by gender in Taiwan, suggesting that more studies are needed to understand social capital’s effects in Asian societies and the mechanisms by which the effects may vary with gender.
Ó 2008 Elsevier Ltd. All rights reserved.
Introduction
The concept of social capital has received great attention in the area of public health research. Studies have consis-tently shown that social capital is related to a variety of health behavior and health outcomes including criminal
behavior, mental health, smoking, self-rated health, mor-bidity, and mortality (DeSilva, Huttly, Harpham, & Kenward, 2007; Kawachi, Kennedy, Lochner, & Prothrow-Stith, 1997; Siahpush et al., 2006; Veenstra et al., 2005). One major cited criticism of prior studies is the lack of examination of differ-ential effects of social capital between genders (Kavanagh, Bentley, Turrell, Broom, & Subramanian, 2006). Most re-searchers ‘‘average’’ the effects of neighborhood-level variables across individuals, despite some evidence that neighborhood effects may be heterogeneous between women and men (Kavanagh et al., 2006; Stafford, Cummins, Macintyre, Ellaway, & Marmot, 2005). Another criticism is a lack of studies conducted in non-Western societies (DeSilva et al., 2007; Mitchell & Bossert, 2007; Yip et al., 2007). Although a large number of studies have suggested a positive relationship between social capital and individual health, whether social capital has a beneficial impact on
q This study was supported by the National Science Council of Taiwan (Grant No. 94-2314-B-038-059). Data analyzed in this paper were col-lected by the research project ‘‘Taiwan Social Change Survey’’ sponsored by the National Science Council. Taiwan Social Change Survey was carried out by the Institute of Sociology, Academia Sinica. The Center for Survey Research of Academia Sinica is responsible for the data distribution. The authors appreciate the assistance in providing data by the institutes and individuals aforementioned.
*Corresponding author. Tel.: þ886 2 27361661x6527; fax: þ886 2 27396814.
E-mail addresses: yingchih@tmu.edu.tw (Y.-C. Chuang), adinma@ tmu.edu.tw(K.-Y. Chuang).
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Social Science & Medicine
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individual health in societies other than the US and Euro-pean countries remains inconclusive. This study examines whether the effects of social capital on individual smoking and drinking behavior varied by gender in Taiwan.
Similar to other ethnic Chinese societies, the society in Taiwan is founded on human relationships (Hwang, 1987). Social networks composed of immediate and ex-tended families, friends, and neighbors form the basis of Chinese societies. Studies have shown that social contacts generated from the dense social networks in Chinese com-munities can effectively lessen economic hardships and psychological distress and are major resources that Chinese individuals use to accomplish their personal goals (Liang & Bogat, 1994; Taylor et al., 2004). However, the close interpersonal relationships also impose heavy duties, obli-gations, and moral standards on individuals, which can confine a person’s expressions and liberties (Portes, 1998). Little is known about whether or how much social capital can increase one’s health in an ethnic Chinese society. In the last two decades, Taiwan underwent rapid economic growth, with an increase of GDP per capita from US$2348 in 1980 to US$14,519 in 2000 and US$16,030 in 2007. Tai-wan thus serves as a good case to examine the health effects of social capital in a society undergoing rapid social transformation. Findings from Taiwan can offer insights into the situations of other countries with similar socioeconomic and cultural backgrounds.
We used smoking and drinking as outcomes of interest because both of these types of behavior are sensitive to the impact of social capital and are prevalent among males in Taiwan (Poortinga, 2006; Siahpush et al., 2006). Similar to other Asian countries, smoking and drinking by male adults in Taiwan are accepted social practices, which serve to establish and maintain interpersonal and social bonds. Of-fering cigarettes and alcohol to others are common at social gatherings such as parties, weddings, and funerals. On many social occasions, men are expected to exchange ciga-rettes, help each other to light up cigaciga-rettes, pour wine for others, and encourage each other to ‘‘bottom up’’ the wine. On the other hand, turning down offers of cigarettes and al-cohol is considered to be rude, which may promote compulsory smoking and drinking behavior in these social contexts. Although smoking and drinking play major roles in social life for men, women are not encouraged to smoke and drink in Taiwan. Women are more likely to reject offers of cigarettes and alcohol without offending others. Al-though women consistently have lower rates of smoking and drinking than men, the prevalence rates of these behavior are increasing due to greater economic indepen-dence and changes in social concepts (Liang, Kuo, & Wang, 2002). The smoking rate of women, in particular, increases from 2.3% to 4.3 % between 1990 and 2000 com-pared to a decreased rate of men from 50% to 43.5%. In the last two decades, rapid socioeconomic changes, such as the massive movement of women into the paid workforce, have altered the roles of women and indirectly promoted female smoking and drinking (Liang et al., 2002). This trend is also reflected in the marketing strategies used by tobacco and alcohol companies, in which liberation, glamour, and elitism are used for the female market (Morrow & Barraclough, 2003a, 2003b).
The concept of social capital
Three major theoretical foundations of social capital are frequently cited in the public health research literature. Putnam (1993, 2000)defined social capital as ‘‘features of social organization such as networks, norms and social trust that facilitate coordination and cooperation for mu-tual benefit’’. He conducted research in both Italy and the US on the relationships among social relations, civic engagement, and political and economic outcomes. In Italy, he found that regions with higher levels of civic engage-ment such as newspaper readership, voter turnout, and membership in various associations had better political and economic performances. He later applied the concept of social capital to analyze US society over the past 20 years and found that a decline in civic cultures led to worsened population health (Putnam, 2000, 1993).
Coleman (1988)described social capital as being imbed-ded in social relationships and serving as resources for people to achieve their interests (Coleman, 1988). Coleman introduced various forms of social capital including (1) ob-ligations, expectations, and trustworthiness that exist in social structures; (2) information channels imbedded in so-cial relationships; and (3) norms and effective sanctions against deviant behavior. Bourdieu (1986), in contrast, introduced three kinds of capital: human capital (i.e., edu-cation), cultural capital (i.e., language), and social capital, defined as a form of group resources that accrue to individuals as a result of their membership in social net-works (Bourdieu, 1986). He suggested that social capital is often used to obtain human capital and cultural capital, which can raise one’s social position and status in a society. According to reviews of the social capital literature, the major differences among Putnam, Coleman, and Bourdieu lie on the definition of social capital as forms, channels, or contents (Carpiano, 2006). Some researchers suggested that Putnam addressed social capital as trust and reciproc-ity in social networks that form the basis through which individuals build up and maintain interpersonal connec-tions, while Bourdieu emphasized that social capital refers to the actual resources that are imbedded in social net-works (Carpiano, 2006). To better distinguish dimensions of social capital, it has been categorized into cognitive and structural resources (Harpham, Grant, & Thomas, 2002). Cognitive social capital refers to subjective percep-tions of the quality of social relapercep-tionships such as trust, support, norms, and reciprocity, while structural social capital refers to the objective quantity of social relation-ships and activities such as membership in associational activities (Mitchell & Bossert, 2007). In addition to the cognitive and structural distinctions, some researchers have categorized social capital into bonding, bridging, and linking forms of social capital (Szreter & Woolcock, 2004). Bonding social capital refers to the relationships among members of a network who see themselves as be-ing similar (i.e., kin family networks). Prior studies used personal contacts with neighbors and friends to measure bonding social capital (Rojas & Carlson, 2006). Bridging social capital refers to links across different groups that do not have similar statuses and identities, such as partic-ipation in culture diversity clubs or organizations. Linking
social capital points to connections to formal and institu-tionalized power in a society. Examples of linking social capital with power structures are voting participation and political action (Lofors & Sundquist, 2007). Szreter and Woolcock (2004) argued that three forms of social capital are important to people’s health: bonding social capital for interpersonal social contact, bridging social cap-ital for solidarity and mutual respect across different social groups, and linking social capital for trusting relationships across groups with different levels of power.
Gender differences in the relationship between social capital and individual health
There is some evidence that the effects of social capital may vary by gender. For example, Locher et al. (2005) found that when social capital was measured by regular religious participation and trust in a community, it had protective effects on the poor nutritional health for black men; however the same effect was not found for black women (Locher et al., 2005). Another study reported that while social trust had positive effects on the self-rated health of men, neighborhood safety and political participa-tion had positive effects on the self-rated health of women (Kavanagh et al., 2006). Similarly,Ellaway and Macintyre (2007) reported that women and men were influenced by different aspects of social capital. Being involved in church-related activities or other social clubs was associ-ated with a lower waist–hip ratio in women only, whereas men being involved in social clubs was related to a poorer body-mass index (BMI) and systolic blood pressure, but better mental health (Ellaway & Macintyre, 2007).Stafford et al. (2005) also found significant interactions between gender and social capital on individual health. They used trust, integration into the larger society, and participation in left-wing society as proxies for social capital. They found that the magnitude of the relationship between social capital and health was larger for women than for men (Stafford et al., 2005).
The above studies showed inconsistent findings of gen-der differences in the relationship between social capital and health. Since different geographical scales were used to measure social capital (i.e., individual, neighborhood, county, state), it is not surprising that they reached differ-ent conclusions. If neighborhoods were used as the unit of measurement, the influences of social capital should largely depend on the length of exposure and the sensitiv-ity to local environments. Traditionally, women are more likely to spend more time in neighborhoods conducting domestic works such as shopping for groceries near by or taking care of children and the elderly (Kavanagh et al., 2006). Women are also likely to be more capable of creating and maintaining local social networks that connect families and communities, given their social role of interpersonal caring and comforting (Warr, 2006). Therefore, we do expect to see the influences of social capital on smoking and drinking to be greater for women than for men because women are more sensitive to and are more likely to be affected by the behavior, norms, and attitudes related to smoking and drinking in their communities.
Social capital and smoking and drinking behavior Only a few studies have investigated the influences of social capital on individual smoking and drinking behavior. According to these studies, the possible mechanisms of so-cial capital on smoking and drinking behavior can be via community norms against tobacco and alcohol use, com-munity organization and collective actions to prevent smoking and heavy drinking (i.e., smoking restrictions in local restaurants); cohesive social networks to buffer the adverse effects of stress, and promotion of more rapid dif-fusion of anti-smoking and anti-heavy drinking messages in communities. Several studies found significant effects of social capital on smoking.Siahpush et al. (2006)found that residing in a community with a higher level of social capital, measured by trust and safety, was related to a higher probability of smoking (Siahpush et al., 2006). Pat-terson, Eberly, Ding, and Hargreaves (2004) found that when a geographical area was aggregately rated as a cohe-sive, safe, and good place to live, individuals reported a lower tendency to smoke (Patterson et al., 2004).Greiner, Li, Kawachi, Hunt, and Ahluwalia (2004)found that com-munity rating (i.e., whether the comcom-munity was rated as a good place to live) was associated with individual smok-ing (Greiner et al., 2004). In addition, Poortinga found that trust and civic participation each was independently asso-ciated with being a smoker (Poortinga, 2006).
Regarding drinking behavior,Godoy et al. (2006)found that increased social capital, measured by exchanging gifts, and help and participation in community work, was associ-ated with fewer instances of drinking alcohol weekly (Godoy et al., 2006).Weitzman and Chen (2005)reported that college-level time committed to volunteering lowered the opportunities for various drinking behavior problems among college students. These results still held up after controlling for individual-level characteristics (Weitzman & Chen, 2005). Poortinga also provided evidence for the ef-fects of social capital on drinking. He found that both indi-vidual and community-level social capital were associated with moderate drinking (Poortinga, 2006).
The above studies seem to indicate that smoking behavior is more consistently associated with community cohesion and trust, but not with social participation and community involvement (Greiner et al., 2004; Siahpush et al., 2006). Drinking behavior, on the contrary, is associated with social participation in several studies (Godoy et al., 2006; Lind-strom, 2005). In addition, prior studies have shown that trust and social participation can interactively influence individ-ual smoking and drinking. Lindstrom suggested that alcohol consumption and intermittent smoking were positively associated with social participation but were negatively associated with trust (Lindstrom, 2003, 2005). This phenom-enon has been called ‘‘the miniaturization of community’’ because even though a great number of people in the youn-ger generation participate in ideologically more narrowly defined groups and organizations, the number of people who participate in traditional organizations (i.e., church and union) is declining. This shows that the dimensions of social capital may interactively influence smoking and drinking, and high social participation is not necessarily correlated with high trust (Lindstrom, 2003).
This study proposes that gender differences constitute differential social contexts in which influences of social capital on individual smoking and drinking behavior occur. We used indicators of social trust, neighborhood closeness, neighborhood social contact, political influence, and membership in associations to measure social capital. We then investigated whether the effects of social capital on individual smoking and drinking behavior varied by gender in Taiwan.
Methods Data
The individual-level data were from the 1995 and 2000 Taiwan Social Change Surveys (Chang, 2000; Chiu, 1995). A multistage cluster sampling method was used to select adults 20 years and older for the survey. The data collected from 359 township/districts of Taiwan was divided into ten strata according to geographic location and degree of ur-banization. Townships or districts in each stratum were selected by probability proportional to their size (PPS). In each selected township/district, lis (a li is a neighbor-hood-level geographical division created by the Taiwan Census Bureau for studying neighborhoods) and villages were selected by PPS, and individuals were randomly selected in lis and villages. Data were collected by interpersonal interviews using a structured questionnaire. Interviewers were required to attend a standardized 2-day training workshop before conducting interviews. The overall response rate was 67% after excluding ineligible cases. The major reasons for not completing the interview included an inability to find the person (18.3%) and refusal to participate (11.2%). Ten percent of the cases were rechecked for quality control. This study defined neighbor-hoods by li and village with an average of 2000 people and 874 households per neighborhood. They were created by visible boundaries such as streets and rivers, and to be as homogeneous as possible with population characteristics. Neighborhoods in this study, on an average, had 33.4% residents with less than a middle school education (std ¼ 13.2), 9.3% with a college degree (std ¼ 7.8), 5.9% be-ing sbe-ingle-parent families (std ¼ 2.0), 8.5% older than age 65 (std ¼ 4.1), and 26.9% younger than age 18 (std ¼ 4.5). Participants’ reports of social capital indicators were then aggregated to their lis and villages to represent neighbor-hood-level social capital. Only 1% of the respondents were not accurately geocoded to their neighborhoods, resulting in a final sample size of 204 neighborhoods and 3713 people. Informed consent was obtained from each participant. The ethics committee of the National Science Council of Taiwan approved this study.
Measurements Social capital
Our social capital measurements followed Putnam’s conceptualization of social capital, which consists of fea-tures such as interpersonal trust, ties of social networks, and social engagement that foster community and social participation. We did not have survey items to cover
Bourdieu’s conceptualization in which social capital is defined as the actual or potential resources that inhere within social networks or groups for personal benefits (i.e., informal social control) (Carpiano, 2006). Although the adequate level for analysis of social capital is still being disputed, we adopted the definition of social capital as a property of groups to distinguish this concept from indi-vidual-level social support (Kawachi, Kim, Coutts, & Subramanian, 2004). Individual responses for each item of social capital were aggregated to the neighborhood level. Each item was recoded so that a higher value represents a higher level of social capital. An oblique exploratory factor analysis was conducted to examine the dimensions of social capital.Table 1shows that five factors were extracted based on a scree plot decision and the stipulation that Eigenvalues of retained factors had to exceed 1. We used factor scores of indicators to represent social capital mea-surements. Neighborhood closeness was measured by the indicators: (1) number of neighbors’ homes that you regularly visit on a five-point scale; and (2) the feeling that this is a close-knit neighborhood on a four-point scale (r ¼ .86). Political influence was measured by the indicators: (1) citizens can contribute to local/city policies if they want to; and (2) citizens have influences on improving the society on a six-point scale (r ¼ .72). Neighborhood social contact was measured by (1) the frequency of contact with relatives; and (2) the frequency of contact with friends on a six-point scale (r ¼ .69). Social trust was measured by (1) most people cannot be trusted; and (2) it is better not to interact with neighbors to avoid trouble on a six-point scale (r ¼ .63). Social participation was measured by asking respondents to indicate their membership of clubs or asso-ciations. The correlation coefficients among dimensions of social capital ranged from 0.005 to 0.18, suggesting that they were weakly correlated. Although we did not directly assess the validity of the measurements, many items were found to have significant relationships with other theoret-ical concepts in previous studies and thus have construct validity. The items on social trust and membership of organizations were positively correlated with self-rated health (Cheng & Chiang, 2002). The items on neighborhood closeness and frequency contacts with friends, relatives, and neighbors were positively related to individual health and status-based sociable resources (i.e., education, in-come) and assets-based social resources (i.e., home owner-ship;Lin, Fu, & Hsung, 2001; Tsai, 2006). In terms of content validity, our measures cover both cognitive and structural social capital, with similar weight given to each. Within the structural social capital questions, one relates to group membership and one to frequency contacts of friends and relatives. Within the cognitive social capital questions, one is for social trust and the other is for the perception of political influence. The measure on neighborhood close-ness covers both structural and cognitive social capital. Our measurements also tap into bonding, bridging, and linking social capital with questions about bonding relationships with neighbors, friends, and relatives, bridging social capi-tal if they join organizations which connect them to people of a different social identity, and linking social capital through political influences in the larger society. Although we defined social capital as a group property, we controlled
individual-level social capital in the analyses to assess whether the effects of neighborhood-level social capital ex-ist above and beyond individual-level social capital. Smoking and drinking variables
Individual-level smoking was measured by the question, ‘‘On average, about how many cigarettes do you now smoke in a day?’’ with responses ranging from ‘‘no cigarettes’’ to ‘‘more than two packs a day’’ on a seven-point scale. Smok-ing was recoded as 0 for no use of cigarettes and 1 for any use of cigarettes. Individual-level drinking was measured by the question, ‘‘How often do you drink alcohol?’’ on a four-point scale including ‘‘none at all,’’ ‘‘occasionally,’’ ‘‘drink often but rarely get drunk,’’ and ‘‘drink often and often get drunk’’. Drinking was recoded as 0 for ‘‘none at all’’ and ‘‘occasionally’’ and 1 for ‘‘drink often but rarely get drunk’’ and ‘‘drink often and often get drunk’’. Sociodemographic variables
The individual-level SES was calculated from two indi-cators: educational attainment and monthly household income. Education was measured by asking respondents, ‘‘What is the highest level of formal education you have completed?’’ with responses ranging from ‘‘less than ele-mentary school’’ to ‘‘graduate school’’ on a seven-point scale. Income was measured by asking participants, ‘‘How much is your household’s total income per month, includ-ing income from all household members livinclud-ing with you?’’ with responses ranging from ‘‘<NT$10, 000’’ to ‘‘NT$220,000’’ on a seven-point scale (US$1 z NT$31). A composite SES score was created by averaging levels of ed-ucation and family income for each respondent. The SES score was categorized into ‘‘high’’ versus ‘‘low’’ using a median split. Gender, age (continuous), race/ethnicity (Taiwanese, Hakka, mainlanders, indigenous populations, and others), and marital status (single, married, divorced and separated, and others) were included in the analyses
as control variables. Because more than 70% of people were Taiwanese, we created a dummy-coded variable and used non-Taiwanese as the reference group. Marital status was recoded as 1 ¼ married and 0 ¼ others.
Analysis
We used multilevel models to analyze our data. We used the SAS GLIMMIX to fit multilevel models with a binomial distribution assumption and a logit link. The method of es-timation was a restricted maximum likelihood procedure. Models were firstly fitted with neighborhood-level social capital characteristics. The second stage was to fit models with individual-level social capital and sociodemographic characteristics. In the third stage, models included neigh-borhood-level social capital, individual-level social capital, and sociodemographic characteristics to assess whether the effects of neighborhood-level social capital could be explained by individual-level social capital and sociodemo-graphic characteristics. Lastly, two-way interaction terms of gender and separate neighborhood-level social capital characteristics were added to the model to test whether the effects of neighborhood-level social capital characteristics on smoking and drinking behavior were modified by gender.
Results
Table 2presents smoking and drinking prevalence by sociodemographic characteristics and gender. About 51.2% of men and 5% of women reported smoking cigarettes. About 15.1% of men and 2.6% of women reported drinking frequently. For male smoking, men who were 30–39 years of age, indigenous, with middle school education, with an income between NT$30,000 and NT$49,999, and widowed/divorced were more likely to smoke than their counterparts. Furthermore, individuals living in neighborhoods with a low amount of closeness, low polit-ical influence, low social contact, high social trust, and
Table 1
Factor analysis of neighborhood-level social capital characteristics, Taiwan social change survey, 1995 and 2000
Neighborhood closeness Political influence Neighborhood social contact Social trust Social participation Number of neighbors’
homes that you regularly visit
0.948 0.013 0.064 0.024 0.010 The feelings
that this is a close-knit neighborhood
0.910 0.040 0.087 -0.016 0.005 Citizens can contribute
to local/city policies if they want to 0.096 0.889 0.000 0.044 0.160 Citizens have influences on improving the society 0.131 0.871 0.012 0.041 0.134 The frequency
of contacts with relatives
0.001 0.030 0.884 0.008 0.070 The frequency
of contacts with friends
0.015 0.044 0.860 0.012 0.085 Most people cannot be trusted 0.128 0.085 0.044 0.862 0.104 It is better not to interact
with neighbors to avoid troubles
0.153 0.081 0.042 0.843 0.090
high social participation were more likely to smoke than their counterparts. Regarding female smoking, women who were less than 30 years of age, indigenous, had high school education, had income less than NT$30,000,
widowed/divorced, lived in neighborhoods with low close-ness, low political influence, low social contact, high social trust, and low social participation were more likely to smoke. For male drinking, the pattern is similar to smoking except that those who had an income between NT$50,000 and NT$69,999 and who lived in neighborhoods with high political influence, median social contact, median social trust, and low social participation were more likely to drink. For female drinking, women who were less than 30 years of age, indigenous, had college education, had income between NT$70,000 and NT$99,999, single, lived in neigh-borhoods with high closeness, low political influence, low social contact, high social trust, and low social participation were more likely to drink than their counterparts.
Multilevel modeling results are shown in Table 3for smoking. Models 1–3 are random intercept models in which the mean of the outcome varied by neighborhood. Model 4 is a random slope model in which the coefficient for gender was allowed to vary by neighborhood. Model 1 indicates that the respondents in neighborhoods with higher neighborhood closeness (OR ¼ 1.13) and lower social trust (OR ¼ 0.88) were more likely to smoke. Model 2 shows that individual-level political influence (OR ¼ 0.90) and social trust (OR ¼ 0.82) were associated with a de-creased probability of smoking, whereas individual-level social contact was associated with an increased probability of smoking (OR ¼ 1.14). Individuals characterized as male, younger, and lower SES reported a higher probability of smoking than their counterparts. Model 3 suggests that political influence was associated with an increased proba-bility of smoking, after adjusting for individual-level social capital and sociodemographic characteristics (OR ¼ 1.13); however this effect disappeared after adding interactions between neighborhood social capital and gender in Model 4. Model 4 shows that the effect of neighborhood-level social trust (OR ¼ 0.75) is significant after including interactions between gender and social capital characteris-tics. A significant interaction was found between social trust and gender (
b
¼ 0.29; OR ¼ 1.34).Table 4presents a similar set of multilevel models for drinking. Model 1 shows that higher neighborhood social participation (OR ¼ 1.18) was associated with an increased probability of drinking. Model 2 shows that individual social contact (OR ¼ 1.21) and individual social participa-tion (OR ¼ 1.13) were associated with a higher likelihood of frequent drinking. Individuals characterized as male, younger, non-Taiwanese, and lower SES had a higher prob-ability of drinking than their counterparts. Model 3 shows that neighborhood social participation remained to be positively associated with individual drinking behavior af-ter controlling individual differences (OR ¼ 1.15). Model 4 shows significant effects of neighborhood closeness (OR ¼ 0.57) and social participation (OR ¼ 1.43) and an interactive effect between neighborhood closeness and gender (
b
¼ 0.21; OR ¼ 1.75).Figs. 1 and 2 present the relationship between social capital and level of smoking or drinking by gender, using a median split. Fig. 1 presents the relationship between social trust and smoking by gender. Although women had a lower level of smoking than men in both low-and high-trust neighborhoods, the slopes show that
Table 2
Description of neighborhood-level social capital, individual-level social capital, individual-level characteristics, smoking, and drinking, Taiwan so-cial change survey, 1995 and 2000
Smokinga(%) Drinkingb(%)
Male Female Male Female Total 51.23 5.00 15.15 2.62 Individual characteristics Age 20–29 56.31 9.18 14.78 3.83 30–39 62.06 3.38 17.43 2.86 40–49 53.25 5.07 15.64 2.64 50–59 49.60 2.59 16.00 2.59 ‡60 46.91 5.74 10.68 0.83 Race/ethnicity Taiwanese 54.75 4.15 14.15 2.62 Hakka 57.37 2.96 17.20 1.49 Mainlander 48.59 6.99 15.41 2.19 Indigenous and others 64.86 22.22 35.14 8.20 Education <Elementary 55.91 5.85 8.70 1.47 Elementary 58.12 5.17 18.35 1.95 Middle school 69.33 5.75 21.43 3.10 High shool 57.28 6.23 15.67 2.92 ‡College 39.16 2.31 9.52 3.36 Family income <NT30,000 56.64 6.99 14.39 1.89 NT30,000–NT49,999 57.88 4.05 16.08 2.72 NT50,000–NT69,999 55.01 5.90 16.14 2.55 NT70,000–NT99,999 53.03 3.93 13.45 3.28 >NT99,999 48.22 4.04 15.52 2.80 Marital status Single 56.68 8.63 15.46 3.95 Married 53.01 3.32 14.72 2.63 Widowed/divorced/others 59.85 10.39 18.25 1.31 Social capital characteristics
Neighborhood closeness High 50.25 4.75 14.45 3.34 Middle 52.09 4.86 15.19 2.61 Low 60.06 5.41 15.75 1.87 Political influence High 53.51 4.19 15.67 2.42 Middle 54.56 4.17 15.40 2.27 Low 54.63 6.63 14.40 3.17 Neighborhood social contact
High 52.29 4.13 15.65 2.48 Middle 53.22 4.82 16.75 2.67 Low 57.06 6.09 13.15 2.73 Social trust High 56.63 6.49 14.31 3.17 Middle 51.66 5.10 16.11 2.74 Low 54.36 3.44 15.05 1.98 Social participation High 55.38 5.16 14.40 1.62 Middle 53.33 3.92 14.26 3.10 Low 53.96 6.01 16.62 3.20
aSmoking is defined as use of any cigarette.
b Drinking is defined as ‘‘drink often but rarely get drunk’’ or ‘‘drink
neighborhood-level social trust had a stronger decreasing effect on smoking for women than for men. Fig. 2 presents the relationship between neighborhood closeness and drinking by gender. The slopes show that neighborhood closeness had a stronger decreasing effect on drinking for women than for men.
Discussion
Since the government of Taiwan opened the tobacco and alcohol markets to foreign companies in 1987, society has
experienced increases in alcohol use for both men and women. Between 1992 and 1997 the prevalence of drinking at least twice a month increased from 26.1% to 41.4% among men and 5.6% to 10% among women (Lai, 2004). The most current health survey showed that 23.8% of men and 7.6% of women had more than five to seven drinks during a sin-gle occasion every two weeks (Executive Yuan of Taiwan, 2005). The prevalence of male smoking slightly decreased from 50.5% to 46.5% between 1992 and 2002; however, the prevalence of female smoking increased from 2.7% to 4.2% (Cheng, Wen, Tsai, & Tsai, 2002; Yen, Pan, Yen, & Lee,
Table 3
Associations between neighborhood-level social capital, individual-level social capital, individual-level characteristics, and individual smoking, Taiwan social change survey, 1995 and 2000
Model 1 Model 2 Model 3 Model 4 Neighborhood closeness 1.13a** (1.04, 1.23)b 0.99 (0.88, 1.11) 0.94 (0.73, 1.20)
Political influence 1.05 (0.97, 1.14) 1.13* (1.01, 1.25) 1.23 (0.96, 1.56) Neighborhood social contact 1.07 (0.99, 1.16) 1.05 (0.95, 1.16) 1.16 (0.94, 1.42) Social trust 0.88** (0.82, 0.96) 0.95 (0.86, 1.06) 0.75* (0.60, 0.93) Social participation 1.03 (0.95, 1.11) 1.08 (0.97, 1.20) 1.17 (0.93, 1.47) Individual closeness 1.05 (0.96, 1.16) 1.05 (0.95, 1.16) 1.06 (0.95, 1.17) Individual political influence 0.90** (0.82, 0.97) 0.87** (0.80, 0.95) 0.87** (0.80, 0.96) Individual social contact 1.14** (1.04, 1.24) 1.12* (1.02, 1.23) 1.12* (1.01, 1.23) Individual social trust 0.82** (0.75, 0.90) 0.83** (0.76, 0.92) 0.84** (0.76, 0.92) Individual social participation 0.92 (0.84, 1.00) 0.90* (0.83, 0.99) 1.12 (0.89, 1.41) Male/female 30.02** (23.62, 38.11) 30.33** (23.86, 38.56) 31.79** (24.60, 41.07) Age 0.97** (0.97, 0.98) 0.97** (0.97, 0.98) 0.97** (0.97, 0.98) Taiwanese/Non-Taiwanese 0.81 (0.64, 1.02) 0.81 (0.64, 1.02) 0.81 (0.64, 1.02) Individual SES 0.72** (0.66, 0.78) 0.72** (0.66, 0.78) 0.72** (0.66, 0.78) Married/others 0.85 (0.70, 1.04) 0.86 (0.71, 1.05) 0.86 (0.71, 1.06) Gender Neighborhood closeness 1.06 (0.82, 1.38)
Gender Political influence 0.90 (0.69, 1.17)
Gender Neighborhood social contact 0.89 (0.71, 1.11)
Gender Social trust 1.34* (1.06, 1.70)
Gender Social participation 0.91 (0.71, 1.16) *P < 0.05, **P < 0.01.
aOdds ratios.
b95% confidence intervals.
Table 4
Associations between neighborhood-level social capital, individual-level social capital, individual-level characteristics, and individual drinking, Taiwan social change survey, 1995 and 2000
Model 1 Model 2 Model 3 Model 4 Neighborhood closeness 1.02a(0.91, 1.14)b 0.92 (0.79, 1.07) 0.57** (0.41, 0.81)
Political influence 1.03 (0.91, 1.17) 1.04 (0.91, 1.19) 1.14 (0.84, 1.56) Neighborhood social contact 0.99 (0.87, 1.11) 0.90 (0.79, 1.03) 1.08 (0.80, 1.45) Social trust 0.92 (0.82, 1.04) 0.94 (0.83, 1.08) 0.86 (0.63, 1.17) Social participation 1.18** (1.04, 1.33) 1.15* (1.01, 1.32) 1.43* (1.07, 1.92) Individual closeness 1.03 (0.91, 1.17) 1.06 (0.93, 1.22) 1.06 (0.92, 1.22) Individual political influence 0.97 (0.86, 1.08) 0.96 (0.86, 1.09) 0.97 (0.86, 1.09) Individual social contact 1.21** (1.07, 1.37) 1.25** (1.10, 1.43) 1.25** (1.10, 1.42) Individual social trust 0.96 (0.85, 1.08) 0.98 (0.86, 1.11) 0.98 (0.86, 1.12) Individual social participation 1.13* (1.01, 1.26) 1.08 (0.96, 1.21) 1.08 (0.96, 1.22) Male/female 6.73** (4.86, 9.34) 6.85** (4.96, 9.48) 7.65** (5.37, 10.91) Age 0.98** (0.97, 0.99) 0.98** (0.97, 0.99) 0.98** (0.97, 0.99) Taiwanese/Non-Taiwanese 0.65** (0.63, 0.67) 0.67** (0.50, 0.90) 0.67** (0.49, 0.90) Individual SES 0.83** (0.74, 0.93) 0.82** (0.73, 0.92) 0.82** (0.73, 0.92) Married/others 1.06 (0.80, 1.39) 1.07 (0.81, 1.40) 1.08 (0.82, 1.42) Gender Neighborhood closeness 1.75** (1.21, 2.52)
Gender Political influence 0.89 (0.64, 1.26)
Gender Neighborhood social contact 0.81 (0.59, 1.12)
Gender Social trust 1.12 (0.80, 1.56)
Gender Social participation 0.77 (0.56, 1.07) *P < 0.05, **P < 0.01.
aOdds ratios.
1994). Although the rates of female smoking and drinking are comparatively low in Taiwan, the normative traditions that protect women from the dangers of tobacco and alcohol use are not immutable. With globalization, the transformation of economic structure, women’s liberation movement, and the entry of women into the workforce on a mass scale, the roles and behavior of women are con-stantly changing (Liang et al., 2002). In addition, the tobacco and alcohol industries acknowledge interests in expanding the market to female consumers. They typically use themes highlighting independence, sophistication, glamour, and sexuality in advertising to women and girls in Asia. (Kaufman & Nichter, 2001). The potential for future tobacco and alcohol promotion through liberalized trade suggest an urgent need to recognize the social
consequences of tobacco and alcohol use (Morrow & Barra-clough, 2003b).
Our results partially support the hypotheses that the ef-fects of social capital differ by gender. Because of differences in the samples and outcomes of interest, it is difficult to determine whether our findings are consistent or contradictory with prior research. We found that social trust is relatively beneficial in reducing a woman’s proba-bility of smoking, but that the effect was weaker for men. One explanation may be that women are more likely to be part of tightly bonded social networks that typically result in trusting relationships. They are also more likely to be the people who can be relied upon to provide support to other network members (Kavanagh et al., 2006). Therefore, living in a place with a higher level of trust may have more influence on women than men.
Neighborhood closeness was found to have a stronger decreasing effect on drinking for women than for men. Given that women are likely to spend more time in their neighborhoods, it is plausible that they would benefit more than men from a high level of neighborhood closeness (Kavanagh et al., 2006; Warr, 2006). Another ex-planation may come from the geographical distribution of neighborhoods. Since more than 60% of close-knit neigh-borhoods in our data were located in rural areas, the norms against female drinking in rural communities may explain the stronger negative influence of neighborhood closeness on drinking among women. On the other hand, the culture of city life may increase one’s opportunity to gain access to alcohol. Social gatherings after work are more common among ‘‘professional women’’ in big cities compared to women in other geographical areas of Taiwan. Future re-search needs to clarify this relationship by studying the social context in which women are encouraged to drink.
Regarding the main effects of social capital, most previous studies indicated that a decline in social capital contributes to a prevalence of unhealthy behavior including problem drinking (Wilson, 1987). However, social partici-pation was found to be positively associated with drinking, after controlling for individual-level social capital and soci-odemographic differences. The inconsistency of these findings with prior studies may be because of the way drinking behavior were measured (Lindstrom, 2005). In contrast with prior studies that measured the outcomes of binge drinking or drunk driving, our study measured drinking behavior by asking respondents whether they drink frequently. Another reason for the positive associa-tion between social participaassocia-tion and drinking may come from the drinking culture in Taiwanese society. Taiwanese society tolerates and even encourages considerable alcohol consumption at social events (i.e., weddings) (Liang, Chou, Ho, Shieh, & Yang, 2004). It is highly possible that people who frequently participate in clubs and associations may be involved in various social occasions where alcoholic bev-erages are frequently served. In such social contexts, the provision of alcohol is regarded as a common courtesy. People renew personal bonds or release stress over a drink. Therefore, participation in various associations may increase the opportunities to drink.
Our study found that social capital measured by general trust in people and neighborhood closeness was negatively
Low High
Social Trust
Log Odds of Smoking
Women Men 1 0 -1 -2 -3 -4
Fig. 1. Relationship between neighborhood-level social trust and smoking by gender.
Low High
Neighborhood Closeness
Log Odds of Dinking
1 0 -1 -2 -3 -4 Women Men
Fig. 2. Relationship between neighborhood closeness and drinking by gender.
associated with smoking and drinking behavior respec-tively, while specific social interactions such as participa-tion in associaparticipa-tions was positively associated with drinking behavior. In our analyses, general social trust and neighborhood closeness can be interpreted as a mani-festation of cognitive social capital, which may decrease one’s substance use due to lower levels of stress and anxi-ety inherent in trusting social relationships. On the other hand, participation in associations in Taiwan, which represents the structural dimension of social capital, can increase opportunities for alcohol use. This suggests that structural social capital may form the social context that facilitates drinking norms and provides drinking opportunities.
Our study shows that political influence was neither associated with smoking nor drinking behavior. Since smoking and drinking behavior are more directly related to social relationships and substance using norms of communities, neighborhood-level political influence, com-paratively, can be a distal determinant of smoking and drinking behavior. Therefore, its effect is less likely to be shown in a neighborhood-level social capital study. Our study also found that individual-level social contact had significant effects on smoking and drinking, but neighbor-hood-level social contact did not. This may suggest that individual contact with friends and relatives did promote smoking and drinking behaviors through social activities; however, since not all of the friends and relatives live inside the neighborhood boundaries, using aggregate scores at the neighborhood level may not truly represent neighbor-hood-level social contacts. Future research needs to revise the interview questions to ask specifically where the social contacts take place.
Our findings should be considered in light of the following limitations. First, we did not have longitudinal social capital measurements, which may have generated selection bias (Tienda, 1991). The relationships of social capital and smoking and drinking may be due to the non-random selection of individuals from neighborhoods with different levels of social capital and not because of the influences of social capital. Therefore, the relationships found between neighborhood social capital and smoking and drinking should perhaps be more cautiously inter-preted as associations rather than as evidence of the influences of social capital. Second, the study did not mea-sure all aspects of social capital (i.e., reciprocity). However, we measured five aspects of social capital including neigh-borhood closeness, political influence, neighneigh-borhood social contact, social trust, and social participation and assessed their influences. Future research needs to improve neigh-borhood measurements by including additional aspects of social capital. Third, we measured social participation by respondents’ reports of membership of organizations. This item has been criticized in having a masculine bias because men are more likely to participate in formal orga-nizations and tend to ignore women’s contributions in the participation in informal network-building activities (Healy, Haynes, & Hampshire, 2007). Future research needs to develop gender-specific indicators for the domain of social participation. Fourth, our findings are subject to correlation errors whereby the associations between
aggregate levels of social capital and individual smoking or drinking behavior may have been falsely inflated since the measures are from the same data source.
Conclusions
These limitations aside, this study suggests that social capital may directly and interactively influence individual smoking and drinking behavior regarding gender. Future research is needed to identify possible mechanisms by which social capital differentially influences health behav-ior between genders in the context of the Asian society. Examples of these mechanisms are women and men’s varying exposure to different aspects of neighborhood lives, types and patterns of their local social networks, and their psychological responses to the quality of neighborhood environment.
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