“Why treat people’s illness without changing what makes them sick in the first place?” World Health Organization poses this question, suggesting that without modifying the social determinants of health, health care and medicine may be useless 1. Social determinants of health examines why, in countries all over the world, there is a social gradient when it comes to health status and outcomes. Individuals higher up in the social hierarchy consistently have better health outcomes than those lower down.

Social capital was explored as a social determinant of health in the public health domain and has become a popular topic in the past decade particularly with the publication of Putnam’s Bowling Alone (2000). Robert Putnam defined social capital as social networks and the associated norms of reciprocity, which is inhering both in the individual and the collective 23. Ichiro Kawachi attempted to normalized definitions and methodologies of measurement of social capital in the health field 45. In Kawachi’s definition, social capital can be examined as a group or community-level characteristic, called “social cohesion”, or as an individual characteristic using network theory. He also separated bonding and bridging social capital. Bonding social capital refers to the social connectedness within a group whose members are alike in some ways (i.e. race or ethnicity, class, language) and bridging social capital is social connectedness that crosses groups or other boundaries of social attribute 6.

A growing body of literature has analyzed the concept of social capital and its impact on health outcomes and has attracted the attention of both the academic and the policy communities. For example, greater social capital has been shown to be associated with better levels of general health and (subjective) well-being, lower cardiovascular and cancer mortality, and lower suicide rates 78910111213.

In this paper, we will explore social capital from the perspective of an individual resource and social connectedness, which refers to the relationships people have with others ^a. People enjoy constructive relationships with others in their families, communities, churches, and workplaces. Families support and nurture those in need of care. Social connectedness is integral to wellbeing. People are defined by their social roles, whether as partners, parents, children, friends, caregivers, teammates, staff or employers, or a pile of other roles. Relationships give people support, happiness, contentment and a sense they belong and have a role to play in society 14. They also mean people have support networks in place that they can call on for help during times of illness or poor health.

Most of the recent studies found a positive relationship between social capital and health in general, but they are limited to descriptive studies. The focus in this paper is on a theoretical approach to the role of social capital in producing health based on Becker’s household production function. This study is testing whether social capital has a positive impact on health status both directly through a more effective production of health and indirectly through utilizing the health care system better, using several measurements of social capital from the National Health and Nutrition Examination Survey (NHANES) 2007-2008 for a sample of those 60 years old and above ^b.

A main reason to consider social capital in light of social networks/ connectedness of elderly people is that networks might enhance positive outcomes for seniors. Previous research reflects strong themes about the importance of family members and friends in the lives of older adults. Social ties have been linked to beneficial health and social outcomes, to the maintenance of independence in later life, and to responsive care for seniors with chronic long-term health problems 151617. It is also timely to examine the relationship between social capital and better heath in elderly people with the advent of the baby-boom generation’s aging and retirement. However, there has been little research on the impact of social connectedness in older adults, except Keating et al. 18.

In the literature, studies utilize subjective self-rated health status to explore the relationship between social capital and health. However, NHANES 2007-2008 allows us to use several objective measures, including medical and laboratory examination results as well as self-rated health status. These objective measures will allow us to conduct a more rigorous study about the impact of social capital on health outcomes.

The proximate determinants of an individual’s health usually are decisions made by the individual or by the household in which people live- given assets, prices, and community endowments. Therefore, a natural starting point is the determination of individual health at the household level. Similar to Behrman and Deolalikar (1988), this project is based on the standard household model with constrained maximization of a joint utility function 1920. It is assumed that the household behaves as if it maximizes a utility function, which is a function of the goods and services consumed, health status of household members, and leisure ^c.

A household behaves as if maximizing a utility function:

(1)

where

is the health of household member i ,

is the consumption of household member i ,

is the leisure of household member i , and

is the number of individuals in the household.

(All of these variables and others defined below may be vectors with multiple dimensions.)

Health is a household-produced commodity. The health of the given i ^th individual is produced by a number of choices relating to the commodities consumed, health inputs, which do not affect utility except through health (e.g. health insurance), and the individual and household endowments:

(2)

where

is the health outcome of the i ^th individual,

is the consumption of the i ^th individual that affects health,

is the observable characteristics including socio-demographic variables of the i ^th individual

is the unobservable attributes, such as genetic endowment of the i ^th individual,

is the characteristics of household, and

is the social capital of i ^th individual .

To analyze the basic correlation between social capital and health, we estimate the following regression:

(3)

where H*_i is the individual's actual health, x is a vector of explanatory variables, S is a vector of social capital, β' is the vector of coefficients, and is the error term. Explanatory variables include socio-demographic variables and genetic endowment variables (X), and social capital (S). Detailed variable lists are found in the appendix.

Data.

The National Center for Health Statistics (NCHS), part of the Centers for Disease Control and Prevention (CDC), has collected nationally representative health and nutrition surveys since the early 1960’s. In each survey a nationally representative sample of the US civilian non-institutionalized population was selected using a complex, stratified, multistage probability cluster sampling design. Primary sampling units (PSU) are generally single counties, although small counties are combined to meet a minimum population size. Clusters of households are selected, the households are screened for demographic characteristics, a sample of households is selected, and one or more persons per household are selected ^d.

Survey workers collected demographic data and information on general health, use of health services, and housing characteristics in an interview in the home. Nearly three-quarters of the participants also received a four-hour medical examination at a mobile Medical Exam Center (MEC). The MECs, including 12 physicians and other persons involved with the examinations, moved from city to city, preserving consistency in the medical exam. In addition to the MEC examinations, a small number of survey participants receive an abbreviated health examination in their homes because they are not able to come to the MEC. The survey included many tools to induce those selected for the study to participate, especially those selected for the medical exam portion of the survey.

For NHANES 2007-2008, 10,149 persons were interviewed and 9,762 were examined in the MEC. Data were collected between January 2007 and December 2008. The data and corresponding documents for the survey interview and examination components are available from the CDC website.

NHANES household, interview, and examination data files were merged using the unique sequence number given to each participant. Samples were weighted using the procedure recommended in the NHANES documentation. In this study, a sample of those 60 years old and above will be analyzed. The total sample size is 1,684 and 815 of them are males and 869 are females. Table 1 shows the definition of variables used in this study.

We have obtained MLE estimates of the coefficients for the probit regressions with instrumental variables predicting overall health status, physical health and mental health during the past 30 days separately ^j. The last two dependent variables can imply recent illness. 2SLS was utilized to obtain the estimate of the coefficients predicting index of biological risk factors. Regression results of the health demand equation are presented in Table 5-1 to Table 5-4.

In general, blacks and Mexican Americans are in poorer health than whites. A similar pattern holds for people who were born in Mexico compared with U.S. born. Each table includes 5 separate regressions with one of five social capital measures: numbers of emotional support sources, emotional support from any source, financial support from any source, either emotional or financial support from any source, and number of close friends. Surprisingly, the social capital measures do not show significant results except in one case. The only exception is that more resources of emotional support can promote better overall health status, as shown in equation 1 in Table 5-1.

Social capital, at least in terms of the variables that are available to measure in the NHANES 2007-2008, do not affect health outcomes of elderly people, at least the ones analyzed in this study. This unexpected finding does not necessarily imply social capital has little impact on health of elderly people. Rather, it opens further questions of refining the models and statistical analysis, including exploring other omitted variables. Maybe our instrumental variable was not suitable for the analyses. Or we may have to accept that the basic hypothesis regarding the effect of social capital on health may simply be rejected in this particular case.

In terms of future research on this topic, we plan to use factor analysis to extract common factors in defining social capital. Factor analysis is a method of data reduction. It does this by seeking underlying unobservable (latent) variables that are reflected in the observed variables (manifest variables). In this study, we used a summary index of biological risk factor using nine indicators. We will utilize other indexing methods and define separate inflammation risk, metabolic risk, and cardiovascular risk with other measures ^k.