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Education, Personal Control, Lifestyle and Health: A Human Capital Hypothesis

July 1998
Research on Aging 20(4):415-449

DOI:10.1177/0164027598204003

Authors:

University of Texas at Austin

The concept of human capital implies that education improves health because it increases effective agency. We propose that education's positive effects extend beyond jobs and earnings. Through education, individuals gain the ability to be effective agents in their own lives. Education improves physical functioning and self-reported health because it enhances a sense of personal control that encourages and enables a healthy lifestyle. We test three specific variants of the human-capital and learned-effectiveness hypothesis: (1) education enables people to coalesce health-producing behaviors into a coherent lifestyle, (2) a sense of control over outcomes in one's own life encourages a healthy lifestyle and conveys much of education's effect, and (3) educated parents inspire a healthy lifestyle in their children. Using data from a 1995 national telephone probability sample of U.S. households with 2,592 respondents, ages 18 to 95, a covariance structure model produces results consistent with the three hypotheses.

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Education, Personal Control,

Lifestyle and Health

A Human Capital Hypothesis

JOHN MIROWSKY

CATHERINE E

. ROSS

Ohio State University

The concept of human capital implies that education improves

health because it

increases effective agency

. We propose that education's positive effects extend

beyond jobs and earnings

. Through education, individuals

gain the ability to be

effective agents in their own lives

. Education improves physical functioning and

self-reported health because it enhances a sense of personal control that encourages

and enables a healthy lifestyle

. We test three specific variants of the human-capital

and learned-effectiveness hypothesis

: (1) education enables people to coalesce health-

producing behaviors into a coherent lifestyle, (2) a sense of control over outcomes in

one's own life encourages a healthy lifestyle and conveys much of education's effect,

and (3) educated parents inspire a healthy lifestyle in their children

. Using

data from

a 1995 national telephone probability sample of U

. households with 2,592 respon-

dents, ages 18 to 95, a covariance structure model produces results consistent

with

the three hypotheses

How does education foster health?

The concept of human capital

implies that education improves health because it increases effective

AUTHORS' NOTE

: The National Institute on Aging (NIA) funded the

survey of "Aging,

Status and the Sense of Control" with grant ROI AG12393 to John Mirowsky and Catherine E

Ross

. The data were collected by the Survey Research Laboratory of the

University of Illinois

This analysis was supported by NIA and by the Department of Sociology

and the College of

Social and Behavioral Sciences at Ohio State University

As coauthors, we thank Madonna

Harrington Meyer, Patricia Drentea, and Maciek Slomczynski

for their comments

. Address

correspondence to John Mirowsky, Department of Sociology, 300 Bricker Hall,

190 North Oval

Mall, Columbus, OH 43210-1353

;

-mail

: mirowsky

.ed u

RESEARCH ON AGING, Vol

. 20 No

. 4, July 1998 415-449

C 1998 Sage Publications, Inc

415

4 1 6

RESEARCH ON AGING

agency on the part of individuals

. According to the theory, education

develops habits, skills, resources, and abilities that enable people to

achieve a better life

. To the extent that people want health, education

develops the means toward creating that end through a lifestyle that

promotes health

. Thus, health is not just a lucky but unintended

consequence of the prosperity that is contingent on education

. In this

article, we extend human capital theory beyond the economic concerns

of productivity and wages to individual health

. We define and test three

specific variants of a human capital theory of learned effectiveness

that education enables people to coalesce health-producing behaviors

into a coherent lifestyle, that a sense of control over outcomes in one's

own life encourages a healthy lifestyle and conveys much of educa-

tion's effect, and that educated parents pass on a healthy lifestyle to

their children

A great deal of evidence suggests that educational attainment leads

to better health

. Education increases physical functioning and subjec-

tive health among adults of all ages and decreases the age-specific

rates of morbidity, disability, and mortality (Feldman et al

. 1989

; Fox,

Goldblatt, and Jones 1985

; Guralnik et al

. 1993

; Gutzwiller et al

. 1989

;

Kitagawa and Hauser 1973

; Kunst and Mackenbach 1994

; Pappas et

. 1993

; Ross and Wu 1995, 1996

; Williams 1990

; Winkleby et al

1992)

. The positive association between educational attainment and

health is largely due to the effects of education on health, not vice versa

(Doornbos and Kromhout 1990

; Wilkinson 1986), and few social

scientists studying health would find reason to doubt that educational

attainment improves health

. The question is how

Human Capital and Learned Effectiveness

EDUCATION AND HUMAN CAPITAL

Formal education indicates investment in human capital-the pro-

ductive capacity developed, embodied, and stocked in human beings

themselves (Schultz 1962

; Becker 1962, 1964)

. According to theory,

formal education develops skills and abilities of general value rather

than firm-specific ones that are of value to a particular employer

(Becker 1962

; Schultz 1962)

. An individual who acquires an education

Mirowsky, Ross / EDUCATION AND HEALTH

can use it to solve a wide range of problems

. Some are the problems

of productivity that concern employers and economists

. Some are

problems in which economic prosperity is one of several means

toward a more basic end

. Health is one of those basic ends

Schooling builds the real skills, abilities, and resources

called

human capital on several levels of generality

. At the most general level,

education teaches people to learn (Hyman, Wright, and Reed 1976)

It develops the ability to write, to communicate, to solve problems, to

analyze data, to develop ideas, and to implement plans (Hyman et al

1976

; Hyman and Wright 1979

; Kohn and Schooler 1982

; Nunn,

Crockett, and Williams 1978

; Spaeth 1976)

. It develops broadly useful

analytic skills such as mathematics, logic, and-on a more basic

level-observing, experimenting, summarizing, synthesizing, inter-

preting, classifying, and so on

. In school one encounters and solves

problems that are progressively more difficult, complex, and subtle

The more years of schooling, the greater the cognitive development,

characterized by flexible, rational, complex strategies of thinking

(Hyman et al

. 1976

; Kohn and Slomczynski 1993

; Nunn et al

. 1978

;

Pascarella and Terenzini 1991

; Spaeth

1976) . Higher education

teaches people to think logically and rationally, to see many sides of

an issue, and to analyze problems and solve them (Pascarella and

Terenzini 1991)

. In addition, the occupational skills learned in school

have generic value

. People learn journalism, biology, engineering,

social work, geology, psychology, business, nursing, and so on

. In

school students learn to tailor the general means of solving problems

to a specific set of problems commonly encountered in an occupation

Education also develops broadly effective habits and attitudes such

as dependability, judgment, motivation, effort, trust and confidence

(Kohn and Slomczynski 1993), as well as skills and abilities

particular the process of learning creates confidence in the ability to

solve problems

. Education instills the habit of meeting problems with

attention, thought, action, and perseverance

. (Some call orientations

such as self-directedness and perseverance "personality traits" [Kohn

and Slomczynski 1993]

.) Thus, education increases effort, which like

ability is a fundamental component of problem solving (Wheaton

1980)

. Apart from the value of the skills and abilities learned in school,

the process of learning builds the confidence, motivation, and self-

assurance needed to attempt to solve problems

RESEARCH ON AGING

The theory of human capital suggests three hypotheses about

education and health

: that education enables people to coalesce health-

producing behaviors into a coherent lifestyle, that a sense of control

over outcomes in one's own life encourages a healthy lifestyle and

conveys much of education's effect, and that educated parents inspire

a healthy lifestyle in their children

. The following sections detail these

hypotheses and the theory and facts relevant to them

DESIGNING A HEALTHY LIFESTYLE

The human capital theory of learned effectiveness suggests that

educated, instrumental people merge otherwise unrelated habits and

ways into a healthy lifestyle that consequently behaves as a coherent

trait

. In theory, education makes individuals more effective users of

information

. Education encourages individuals to acquire information

with intent to use it

. Thus, the more educated may assemble a set of

habits and ways that are not necessarily related except as effective

means toward health

Purposeful individuals may coalesce a healthy lifestyle from other-

wise incoherent or diametric practices allocated by subcultural forces

Individuals tend to do whatever others like them to do, particularly if

it distinguishes the people they identify with from the ones they do

not

. Some of those things make health better and some make it worse

For example, men exercise more frequently than women

; women

restrict body weight more closely than men (Hayes and Ross 1986

;

Ross and Bird 1994)

. Likewise, young adults smoke more than older

adults but also exercise more (Hayes and Ross 1986

; Ross and Bird

1994

; Ross and Wu 1995)

. Individuals putting together a healthy

lifestyle must adopt the healthy habits of men and women, young and

old

. In doing so they create positive correlations among traits that

otherwise might be uncorrelated or even negatively correlated

Some evidence supports the ideas that education encourages

healthy behaviors and pulls together the healthy elements from the

lifestyles of various subpopulations

. Compared to those with little

schooling, well-educated persons are more likely to exercise, are more

likely to drink moderately rather than abstain or drink heavily, and are

less likely to smoke or be overweight (Ross and Bird 1994 ; Ross and

Wu 1995)

. Exercise is associated with better health

. Smoking, excess

Mirowsky, Ross / EDUCATION AND HEALTH 419

body weight, and heavy drinking or abstention from drinking are

associated with poorer health (National Center for Health Statistics

1989

; Berkman and Breslow 1983

; Berlin and Colditz 1990

; Leon et

. 1987 ; Manson et al . 1995

; Paffenbarger et al

. 1993

; Sandvik et al

1993

; Segovia, Bartlett, and Edwards 1989

; Surgeon General 1982

;

. Preventive Services Task Force 1989

; Guralnik and Kaplan 1989

;

Gaziano et al

. 1993

; Stampfer et al

. 1988)

. Thus, the evidence suggests

that education may encourage and enable people to create a healthy

lifestyle from diverse sources

The health behaviors associated with higher education show little

consistent relationship to other sociodemographic traits

. Only educa-

tion correlates positively and consistently with healthy behaviors

THE SENSE OF CONTROL LINKING

EDUCATION TO A HEALTHY LIFESTYLE

The better educated may enjoy better health in part because educa-

tion increases the agency and personal control that motivates people

to design a healthy lifestyle

. The theory of human capital converges

with the theory of personal control in many ways

. Through formal

education people learn to solve problems and to be active and effective

agents in their own lives (Mirowsky and Ross 1989

; Wheaton 1980)

People who feel in control of their own lives seek information by

which to guide their lives and improve their outcomes

. Logically, then,

people who feel in control of their own lives tend to adopt a lifestyle

that produces health . By developing personal control and effective-

ness, education develops individuals who seek and discover a healthy

lifestyle

The sense of personal control therefore may form an important link

between education and health

. Belief in personal control is a learned

expectation that outcomes depend on one's own choices and actions

The individual believes that he or she can master, control, or effec-

tively alter the environment

. On the other end of the continuum, a

perceived lack of control is the learned expectation that one's actions

do not affect outcomes

. The concept of perceived control appears in

the scientific literature in a number of related forms with various

names, including self-directedness (Kohn and Schooler 1982), mas-

tery (Pearlin et al

. 1981), instrumentalism (Wheaton 1980), personal

420

RESEARCH ON AGING

efficacy or self-efficacy (Downey and Moen 1987

; Gecas 1989),

personal autonomy (Seeman and Seeman 1983), internal locus of

control (Rotter 1966), and, on the negative side, fatalism (Wheaton

1980), powerlessness (Seeman 1983), helplessness (Seligman 1975),

and external locus of control (Rotter 1966)

Beliefs about personal control generally represent realistic percep-

tions of objective conditions (Mirowsky and Ross 1989)

. High levels

of education increase the sense of personal control (Pearlin et al

. 1981

;

Ross and Mirowsky 1992

; Wheaton 1980)

. In contrast, the poorly

educated may not possess the resources necessary to achieve their

goals, which produces a sense of powerlessness, fatalism, and help-

lessness (Wheaton 1980)

. Education increases learned effectiveness

;

its absence produces learned helplessness

The sense of personal control improves health in part by way of

health-enhancing behaviors

. Compared with people who feel power-

less to control their lives, those with a sense of personal control know

more about health

; they are more likely to initiate preventive behaviors

like quitting smoking, exercising, or moderating alcohol consumption

;

and they have better self-rated health, fewer illnesses, and lower rates

of mortality (Seeman and Lewis 1995

; Seeman and Seeman 1983

;

Seeman, Seeman, and Budros 1988

; Grembowski et al

. 1993)

TRANSMITTING FAMILY HUMAN CAPITAL

If educated people merge healthy habits and ways into a coherent

lifestyle, then their children may assimilate it from them

. Parents who

deliberately choose a healthy lifestyle for themselves may deliberately

raise their children to live that way too

. If so, then the adult children

of more educated parents live healthier lifestyles than others with their

own level of education

There is evidence that higher childhood socioeconomic status in-

creases health and survival in adulthood, but it is not clear why (Elo

and Preston 1992)

. Some research suggests that the effect may work

entirely through the inheritance of socioeconomic status

. High-status

adults who live long and healthy lives tend to come from high-status

families, although the adulthood status may account for the longevity

(Mare 1990)

. Children of better educated parents are less likely to take

up smoking (Flay et al

. 1994)

. Education reduces the probability that

an adult smokes cigarettes, and parents who smoke make it far more

likely that their children will, too (Flay et al

. 1994

; Kandel and Wu

1995)

. There is some evidence that higher parental education lowers

an adolescent's probability of being overweight (Greenlund et al

1996) and that obesity at the end of adolescence predicts mortality

from coronary heart disease in late middle age (Elo and Preston 1992)

Research on teenage sexual behavior provides a clear example of

educated parents encouraging two behaviors that are culturally dia-

metric but similarly effective

. Religious and social norms promote

either abstinence or contraception, but the teenage daughters of more

educated mothers are both more likely to abstain and more likely to

use contraception if sexually active (Cooksey, Rindfuss, and Guilkey

1996)

On the whole there is not much direct evidence for or against the

proposition that educated parents transmit a coherent health lifestyle

to their children

. However, well-educated parents may equip their

children with resources that affect their health as adults

. Hypotheti-

cally, the child of well-educated parents may learn healthy habits in

the family of origin that ultimately improve health

. If so, then parental

education will affect a person's lifestyle net of the person's own

educational attainment

OTHER LINKS TO HEALTH

Economic resources

The theory of human capital suggests that

education improves health by enhancing effective agency

. However,

education might simply allocate individuals to social positions with

more or less access to society's wealth

. A higher education increases

an individual's expected income, thus reducing the likelihood of

severe economic deprivation

. Poverty undermines health and in-

creases the rates of impairment, disability, disease, and death (Angell

1993 ; Epelbaum 1990 ; Mirowsky and Hu 1996

; Pappas et al

. 1993

;

Rogers 1992

; Sorlie, Backlund, and Keller 1995

; Williams 1990)

Indeed, poverty may be defined as lack of the means to provide for

material needs (Mirowsky and Hu 1996)

Even if education were nothing more than a lottery, the outcome of

that lottery would be prosperity, health, and long life for some

;

impoverishment and poor health for others

. Conflict theorists such as

Mirowsky, Ross / EDUCATION AND HEALTH

2 1

RESEARCH ON AGING

Collins (1979) argue that education is an inherently worthless creden-

tial providing no real skills but, because employers use degrees in

hiring, higher education leads to good jobs and high incomes

. Many

conflict theorists speak of education as a mechanism for assigning

individuals to socioeconomic positions that legitimizes the resulting

inequality (Bowles and Gintis 1976)

. Some appear to doubt that

education adds any value in the process, except to make winners and

losers alike see fairness in the outcome (Aronowitz and Giroux 1993

;

Bourdieu 1977

; Bowles and Gintis 1976)

. To them, education func-

tions as a lottery rigged to provide better chances to the children of

high-status families

. In this view education transmits socioeconomic

status from parents to their children, thereby perpetuating

social

inequality, but does not provide generally effective skills and abilities

that individuals use to improve personal outcomes (Bourdieu 1977

;

Bowles and Gintis 1976)

Confirmation of the human capital hypothesis requires more than

a proven effect of education on health

. It requires a demonstration that

part

of education's effect is not mediated by economic status

requires evidence that part of education's impact results from agency

and effectiveness that increase personal control and improve a healthy

lifestyle

. A test of the human capital theory of education and health

must distinguish the effects of education and personal control

lifestyle and health from those of economic well-being

. Effects of

education on health meditated by economic well-being are consistent

with a human capital theory, because high income is one consequence

of the human capital acquired in school

. However, a stringent test of

the human capital hypothesis requires effects of education beyond

those mediated by economic status

Some research on socioeconomic status (SES) and health uses

education and income as interchangeable indicators of socioeconomic

status (Williams and Collins 1995)

. In contrast, we argue that educa-

tion and income indicate different underlying concepts

. Schooling

means something apart from SES

. According a human capital perspec-

tive of learned effectiveness, education indicates the accumulated

knowledge, skills, and resources acquired in school

. Income indicates

economic resources available to people

. Both likely affect health, but

for different reasons

. Furthermore, education and income are not at

the same causal level

. Combining variables from different causal

Mirowsky, Ross / EDUCATION AND HEALTH 423

levels obscures processes

. Part of education's effect may be mediated

by economic status, but if education's sole value to health is due to

economic resources, then the learned effectiveness theory

is not

supported

. To understand the processes by which socioeconomic

status affects health, education and income must be distinguished

Social support

Education and its economic benefits increase the

likelihood of having supportive relationships (Atkinson, Liem,

and

Liem 1986

; Eckenrode 1983

; Gore 1978

; Ross and Mirowsky 1989

;

Turner and Marino 1994)

. Social support improves health and de-

creases mortality (House, Landis, and Umberson 1988)

. It also may

nurture a healthy lifestyle because partners sometimes encourage

exercise or discourage smoking or heavy drinking (Umberson 1987)

Thus, any effects of social support must be distinguished from those

of the factors representing human capital

. Like economic resources,

social support could reflect human capital but also could indicate other

things

. Schooling promotes supportive and equitable relationships

because it helps partners understand and negotiate with each other, see

more than one side of an issue, and respond flexibly with attempts to

understand the other's position and to arrange something

that is

mutually satisfactory

. Hence, human capital gained in school could

improve the ability to build and maintain supportive relationships, but

evidence for human capital theory requires that education's effects go

beyond social support

HYPOTHESES

The theory of human capital suggests three consequences

for

health

. The first states that education improves health in large part

because it enables the fashioning of a healthy lifestyle, the second that

a sense of control over one's own life encourages a healthy lifestyle

and conveys much of education's effect, and the third that more

educated parents transmit a healthier lifestyle to their children

Sample

Our analyses use the 1995 survey of Aging, Status, and the Sense

of Control (ASOC)

. It is a national telephone probability sample of

RESEARCH ON AGING

. households

. The National Institute on Aging supported the data

collection

. Sampling, pretesting, and interviewing were conducted by

the Survey Research Laboratory of the University of Illinois

. Respon-

dents were selected using a prescreened random-digit dialing method

that decreases the probability of contacting a business or nonworking

number and decreases standard errors compared to the standard Mi-

tofsky-Waksberg method while producing a sample with the same

demographic profile (Lund and Wright 1994 ; Waksberg 1978)

. The

ASOC survey has two subsamples, designed to produce an 80%

oversample of persons age 60 or older

. The survey was limited to

English-speaking adults . The main sample draws from all households

;

the oversample draws only from households with one or more seniors

In the main sample the adult (age 18 or older) with the most recent

birthday was selected as a respondent

. In the oversample the senior

(age 60 or older) with the most recent birthday was selected

. Up to 10

callbacks were made to select and contact a respondent, and up to 10

to complete the interview once contact was made

. Interviews were

completed with 71

.6% of contacted and eligible persons

: 73

.0% for

the main sample and 67

.3% for the oversample

. The final sample has

2,592 respondents ranging in age from 18 to 95

. In all, 58% of the

sample is younger than age 60 (n = 1,496) and 42% of the sample is

60 years or older (n = 1,097)

. A large number of older persons ensures

greater variation in health (Verbrugge 1986)

. Since the survey over-

sampled respondents age 60 and older by 1

.8, we weighted the sample

using a weighting variable equal to 1, if age 59 or younger, and

.8,

if age 60 or older

. Because the weighted and unweighted covariance

structure model results were substantively the same, we present the

latter

The following statistics compare the demographic characteristics

of the ASOC sample with those of the whole U

. population

Bureau of the Census 1995)

. The sample statistics are weighted to

compensate for the oversample of seniors

. For ASOC and the United

States, respectively, female respondents were 56

.2% versus 51

.2%

;

White respondents were 85

.1% versus 82

.9%

; married respondents

(excluding cohabitants and the separated) were 55

.7% versus 55%

;

and the mean household sizes were 2

.67 versus 2

.59 people

. For

persons age 25 or older, those with a high school degree were 85

.1 %

versus 80

.9%, and those with a college degree were 25

.6% versus

Mirowsky, Ross / EDUCATION AND HEALTH 425

.2%

. The mean household incomes were $43,949 versus $41,285,

respectively

Measurement

To test the hypotheses we specify and estimate a covariance struc-

ture model that distinguishes constructs from their indicators

. Some

constructs such as gender have a single indicator

. Others such as health

lifestyle have multiple indicators

. This section describes the indicators

of each construct

HEALTH

The health factor is indicated by self-reported health and two forms

of physical impairment

: musculoskeletal impairment and sensory

impairment

Self-reported health is

the respondent's subjective assessment of

his or her general health (coded 1

very poor,

2 = poor, 3 =

satisfactory,

4 =

good,

5 =

very good)

Self-reported health is a valid

and reliable measure of general physical well-being (Davies and Ware

1981

; Mossey and Shapiro 1982)

. It combines the subjective experi-

ence of acute and chronic, fatal and nonfatal diseases, and general

feelings of well-being, such as feeling run-down and tired, having

backaches and headaches

. Thus, it measures health as defined by the

World Health Organization-as a state of well-being and not simply

as the absence of disease

. Self-reported health correlates highly with

more "objective" measures such as a physician's assessments and with

measures of morbidity, and it predicts mortality net of chronic and

acute disease, of physician assessment made by clinical exam,

physical disability, and of health behaviors (Davies and Ware 1981

;

Idler and Kasl 1991

; Liang 1986

; Mossey and Shapiro 1982)

. In fact,

self-assessed health is a stronger predictor of mortality than is physi-

cian-assessed health (Mossey and Shapiro 1982)

Physical Impairment is

assessed, first, by

musculoskeletal impair-

ment,

which describes difficulty with physical mobility and function-

ing in daily activities

. Respondents were asked, "How much difficulty

do you have (1) climbing stairs

; (2) kneeling or stooping

; (3) lifting

426

RESEARCH ON AGING

or carrying objects less than 10 pounds, like a bag of groceries

; (4)

preparing meals, cleaning house, or doing other household work

; (5)

shopping or getting around town?" Responses were

a great deal of

difficulty

(coded 2),

some difficulty

(coded 1), and

no difficulty

culty

(coded

. The index of musculoskeletal impairment averages the responses

to the five questions

. It is similar to Nagi's (1976) disability scale

. The

second form of physical impairment is sensory impairment,

which

assesses difficulty seeing and hearing

. Respondents were asked, "How

much difficulty do you have (1) seeing, even with glasses

; (2) hear-

ing?" (For those with a hearing aid, "hearing, even with your hearing

aid?") Responses and codes are the same as for musculoskeletal

impairment

. The index of sensory impairment averages the responses

to the two questions

. Although all information in surveys consists of

self-reports, physical impairment is less subjective than self-reported

health

EDUCATION

Education

is the reported number of years of formal schooling

Parents 'education

is a factor indicated by the mother's and the father's

years of formal schooling

SENSE OF CONTROL

The sense of personal control is the belief that you can and do

master, control, and shape your own life

. Perceived lack of control,

the opposite, is the expectation that one's behavior does not affect

outcomes

. Sense of control is measured with a crosscutting factor

model that balances statements claiming or denying control over good

and bad outcomes (Mirowsky and Ross 1991)

. The measure is similar

in concept to the personal control component of Rotter's

(1966)

locus-of-control scale and to Pearlin et al

.'s (1981) mastery scale

. The

major difference is that the crosscutting factor model eliminates bias

that might be introduced by the tendency to agree with all statements

regardless of content or by defensive claiming of responsibility for

successes but not for problems (Mirowsky and Ross 1991)

. The factor

has four indicators, each composed of a two-item index

Responsibility

for success

claims "I am responsible for my own successes," and "I

Mirowsky, Ross / EDUCATION AND HEALTH 427

can do just about anything I really set my mind to

Responsibility for

failure

claims "My misfortunes are the result of mistakes I have

made," and "I am responsible for my failures

Denying control over

success

claims "The really good things that happen to me are mostly

luck," and "There's no sense planning a lot-if something good is

going to happen it

will

." Denying control over problems

claims "Most

of my problems are due to bad breaks," and "I have little control over

the bad things that happen to me

." Response categories are

strongly

disagree

(coded

-2), disagree (-1),

agree

(1),

and

strongly agree

(2)

HEALTH LIFESTYLE

The factor representing healthy lifestyle has five indicators

Walking is

measured as the number of days walked per week

Respondents were asked, "How often do you take a walk?" Open-

ended responses are coded into number of days walked per week

Exercise is

an index of moderate and strenuous exercise

. Strenuous

exercise is measured by asking respondents, "How often do you do

strenuous exercise such as running, basketball, aerobics, tennis, swim-

ming, biking, etc

.?" Open-ended responses are coded in number of

days of strenuous exercise per week . Moderate exercise is measured

by asking respondents, "How often do you do moderate exercise like

golf, bowling, dancing, gardening, or playing games with children?"

Open-ended responses are coded in number of days of moderate

exercise per week

. The index averages responses to the moderate- and

strenuous-exercise questions

Being

overweight

is measured by the Quetelet index of weight

relative to height (kg/m

)

Of the various weight-relative-to-height

measures, weight/height' is the most adequate because it is

least

correlated with height and highly correlated with skinfold measures

indicating body fat (Roche et al

. 1981)

. People who are heavier tend

to underestimate their weights, but the bias introduced by using

self-reports is "small and inconsequential" (Palta et al

. 1982

:230

;

Stunkard and Albaun 1981)

. We treat the overweight category as a

continuous variable

. Technically, the index measures relative weight,

but we call it "overweight" because the best health in the sample is

associated with the lowest scores

. While it may be possible to be "too

thin," the problem is rare enough in the general population to ignore

RESEARCH ON AGING

Put another way, the optimum weight for height is not significantly

above the lowest values observed in the sample

. In the sample, 30%

score 27 or higher on the index, which is often used

the cutoff for

obesity (Kohrs et al

. 1979)

. The average man is 5'10" and weighs

183

.9 lbs

; the average woman is 5'4" and weighs 145 .9 pounds

Moderate drinking is

measured by asking, "On average, how often

do you drink any alcoholic beverages such as beer, wine, or liquor?"

and "On the days that you drink, on average, how many alcoholic

drinks do you have?" From these questions, a drinking quantity/

frequency score was computed by multiplying the number of days per

week a person drinks by the number of drinks reported for the average

day

. We then created three categories (abstainers, moderate drinkers,

and heavy drinkers) because the effect of drinking on health

previous research is nonlinear, with both abstainers and heavy drinkers

reporting worse health than moderate drinkers

. Moderate drinkers

average up to 4 drinks per day (28 per week) (54% of the sample)

. A

dummy variable contrasts them with abstainers and heavy drinkers

Abstainers report that they take less than 1 drink per year (44% of the

sample)

. Heavy drinkers average more than 4 drinks per day (2% of

the sample)

Smoking

is represented by a dummy variable coded 1 for persons

who smoke seven or more cigarettes a week and 0 for persons who

never smoked or have quit

CONTROL VARIABLES

Economic resources are measured with household income and

economic hardship

Household income is

coded in thousands of dol-

lars per year

Economic hardship

is a factor with two indicators

Respondents were asked, "During the past 12 months, how often did

it happen that you (1) did not have enough money to buy food, clothes,

or other things your household needed

; (2) had trouble paying the

bills?" Responses categories are

never

(coded

1),

not very often (2),

fairly often (3),

and

very often (4)

Social support

is a factor with two indicators

Emotional support is

indexed by the average level of agreement with the statements that "I

have someone I can turn to for support and understanding when things

get rough," and that "I have someone I can really talk to

Instrumental

Mirowsky, Ross / EDUCATION AND HEALTH 429

support

is indexed by agreement with the statements that "I have

someone who would help me out with things, like give me a ride, watch

the kids or house, or fix something ." The response categories are

strongly disagree

(-2), disagree (-1),

agree

(1),

and

strongly agree

(2)

Gender is

a dummy variable, coded 1 for females and 0 for males

Age

is coded in years

Model

The covariance structure model incorporates measurement and

structural equations estimated using EQS (Bentler 1989)

. The mea-

surement equations of the model specify seven latent factors that

represent parental education, economic hardship, the sense of control,

social support, agreement bias, health lifestyle, and health

. (Agree-

ment bias is a method factor that affects agreement with statements

about control and support

.) The construct equations of the model

specify a block-recursive structural model with the sense of control,

social support, and agreement bias in a block

. The weak causal order

(Davis 1985) hypothesized in the structural equations is as follows

gender, age, and parents' education > education > household income

> recent economic hardship > sense of control and social support (and

agreement bias) > healthy lifestyle > health

. This order represents the

assumptions of the human capital theory

. (Other possibilities and their

implications will be discussed

.) The initial structural model specified

all correlations between disturbances as zero and specified all direct

effects as nonzero if consistent with the order assumptions and as zero

otherwise

The fit of the model was improved by making the following

adjustments (in the order given)

: free any correlation between distur-

bances that the Lagrange multiplier (LM) test suggests is not zero, free

any factor loading that the LM test suggests is not +1 or-1, fix to zero

any structural coefficient that is not significantly different from zero,

free any direct effect of an upstream structural variable on an indicator

of healthy lifestyle or health that the LM test suggests is not zero

the direct negative effect of being female on being overweight)

. Thus,

the final model in Figure 1 and Table 1 is pruned of insignificant effects

and relaxes restrictions on the loadings and disturbance correlations

430

RESEARCH ON AGING

Figure 1

: Education and Health

: Structural Model With Standardized Coefficients

that appear to be inconsistent with the observed covariances

. In

addition, we freed the direct effect of musculoskeletal impairment on

walking, exercising, and being overweight as

described below

There were no signs of underidentification

: Convergence took only

13 iterations, no special problems occurred during optimization, and

no parameter estimates were linearly dependent or constrained at

boundaries . The final model has a

of 543 with 178 degrees of

freedom, a Bentler-Bonnet Normed (BBN) fit index of

.944 and a

Comparative Fit Index (CFI) of

.962, which are above the value of

.900 that is generally considered adequate (Bentler 1989, Byrne 1994)

Results

The structural model shows results consistent with the hypothesis

that education enables people to forge a healthy lifestyle

. The model

implies that education increases health in large part through a healthy

lifestyle

. Figure 1 illustrates the structural model that corresponds to

TABLE I

Construct Equations' of the Covariance Structure Model" (metric coefficients

with t values in parentheses)`

. Measurement equations and the covariances of measurement errors and construct residuals are given in Table 2

. The probability value for the overall fit of the model is

.001(8

= 542

.966,

df=178)

The fit indexes are

.944 (Bentler-Bonett Nonmed),

.950 (Bender-Bonett

Nonnormed), and

.962 (Comparative Fit Index)

. All free coefficients are significantly different from zero atp <

.050 (two-tailed)

. Blanks represent coefficients fixed to zero

. Disturbance between sense of control and agreement correlated -

.451, covariance -

.048, t=-8

.637

Independent Variable

Education

Household

Income

Economic

Hardship

Dependent Variables

Sense of Control

Social Support

Healthy Lifestyle

Health

. Parents' education

.404

.284

.012

(16

.518)

.877)

.011)

. Female

.404

-7

.488

.110

.151

(-3

.873)

(-4

.217)

.024)

(6 .331)

. Age

.011

.006

.007

.011

(-15

.448)

(-11

.109)

(-10

.084)

(-4

.087)

. Education

.772

.047 .047

.021

(10

.595)

(-9,073)

(12

.387) (3 .851) (3

.131)

. Household income

.002

.001

(-7

.893)

.119)

.953)

F Economic hardship

.131

.200

.026

(-7

.455)

(-8

.561)

(-6

.815)

. Sense of control

.371

.838)

. Social support

. Healthy lifestyle

.175

.065)

. Health

.144

.076 .172

.293

.130

.614 .681

432

RESEARCH ON AGING

Table 1

. Health lifestyle mediates the majority of education's total

effect on health, which follows two separate paths

. The one through

healthy lifestyle has a standardized value of

.212 =

.810[

.140 +

.354

(

.321 + (

.099 x

.225) )]

;

the one through economic hardship has a

standardized value of .044 = -

.187[-

.196 + (-

.169 x

.225)]

. The two

paths imply a total standardized effect of

.256

. Health lifestyle thus

mediates about 83% of education's total effect on health in the model

(

.828 = .212 _

.256)

. Low economic hardship accounts for the rest

The measurement model indicates that healthy ways form a coher-

ent lifestyle

. Details of the measurement model shown in Figure 2 and

Table 2 are consistent with the hypothesis that a healthy lifestyle exists

and produces correlation among otherwise disparate ways

. The factor

has nonzero variance

. The factor loadings have the appropriate signs,

consistent with the idea that a healthy lifestyle increases the frequency

of exercise and walking and the probability of moderate drinking

while decreasing excess body weight and the probability of smoking

All the effects of education, parents' education, and the sense of

control on the separate aspects of health lifestyle operate through the

common factor, with only one exception (a direct effect of education

on moderate drinking net of healthy lifestyle, shown in row 12 of

Table 2)

. The measurement model also suggests that a healthy lifestyle

coalesces from otherwise disparate elements

. The standardized coef-

ficients are small, suggesting that most of the variance in each specific

indicator is unrelated to variance in the others

. Four of the

five

indicators of a healthy lifestyle are directly affected by a structural

variable other than healthy lifestyle, such as age or gender (rows

through 15 in Table 2)

. (The direct effects of musculoskeletal impair-

ment on exercise, walking, and being overweight will be discussed

later

.) On the whole, the results for the measurement model

are

consistent with the hypothesis of a coalescent healthy lifestyle

The results in the structural model are consistent with the idea that

a sense of control over one's own life encourages a healthy lifestyle

and transmits much of education's effect

. Education has a significant

positive effect on the sense of control

. The sense of control has a

significant, positive direct effect on healthy lifestyle net of the other

structural variables, as shown in Figure 1 (row G, column I of Table

. The model implies that the sense of control accounts for about 45%

of education's effect on health lifestyle (

.448 = (

.321 x

.354) _ (

.140 +

Mirowsky, Ross / EDUCATION AND HEALTH 433

Figure 2

Healthy Lifestyle and Health

: Detail of the Measurement Model With Stan-

dardized Coefficients

.321 x

.354))

Thus, it also implies that the sense of control's impact

on a healthy lifestyle accounts for about 37% of education's total effect

on health (

.371 =

.448 x

.828)

The results in the structural model support the idea that more

educated parents transmit a healthier lifestyle to their offspring

. The

TABLE 2

Measurement Equations of the Latent-Factor Covariance Structure Model' (metric

coefficients with t values" in brackets)

. Mother's education

. Father's education

.000

. Not enough $ for food,

clothes, etc

.000

. Trouble paying bills

.000

. Responsible for my successes

.000

. Responsible for my failures

.000

.790`

.264

[12

.743]

[-7

.278]

. Good things happen by luck

-1

.000

. Problems are from bad

-1

.000

.790`

breaks I don't control

[12

.743]

. Emotional support

.188

.000

[3 .093]

. Instrumental support

.188

.000

.093]

Observed Independent Variables

Latent Factors

Parents'

Economic

Sense of

Social

Healthy

Observed Measure

Female

Age

Education Education

Hardship

Control

Agreement

Support

Lifestyle

Health

. The model assumes that the residuals of equations and the unique

components of measures are uncorrelated unless a Larange Multiplier

(LM) test suggests

otherwise (Bentler 1989)

. Loadings without corresponding t values are fixed to the values shown

Blanks represent coefficients fixed to zero

. Fixed equal

. Smoke

.006

.243

[-8

.638]

[-3

.383]

. Drink moderately

.023

.319

.602] [3

.820]

. Overweight!

-1 .494

.831

[-8

.151]

[-1

.961]

. Walk

.000

. Exercise`

.036

.000

.981]

. Musculoskeletal impairment

-3

.419

[-15

.977]

. Sensory impairment

-1 .000

. Self-reported Health

.007

.783

.250]

[14

.664]

436 RESEARCH ON AGING

results, illustrated in Figure 1, show that the parents' education has a

significant, positive direct effect on health lifestyle net of the respon-

dent's own education and economic status (row A, column I of

Table 1)

. Adult children of well-educated parents have better health

than the adult children of less well-educated parents, in part because

they have more education themselves, which in turn, improves health

lifestyle, and in part by way of direct effects of parental education on

lifestyle

The structural model also takes into account economic resources

and social support . First, the model indicates that low income and

economic hardship have two negative effects on health

. The larger one

is through the direct effect of economic hardship on health (about 75%

of their total effects in the model)

. The other is through their negative

impact on the sense of control and thus on health lifestyle

. Income,

which is shaped by one's own educational attainment and by one's

parents, affects health by way of economic hardship and sense of

control

. Second, education has a significant positive effect on social

support

. Support, though, has no direct effect on either lifestyle or

health, but it has a substantial unanalyzed residual correlation that

could imply an indirect effect through the sense of control

. These

findings will be discussed below, particularly as they relate to the idea

of human capital and the hypotheses of a coalescent healthy lifestyle,

family human capital, and the sense of control

Other findings that do not bear directly on the main hypotheses

relate to age

. The model indicates that age has a large negative effect

on healthy lifestyle that accounts for the negative correlation between

age and health

. Part of the negative effect of age on health lifestyle is

direct and part is indirect through a low sense of control

One subordinate aspect of the measurement model must be noted

Musculoskeletal physical impairment (which includes difficulty

climbing stairs, kneeling, stooping, carrying, and getting around) has

significant negative direct effects on exercising and on walking and a

significant positive direct effect on the extent of being overweight

(See Figure 2 and rows 16 through 18 of Table 2

.) We specified these

effects on a hypothetical basis, to eliminate any bias that might result

from the impact of difficulty moving as an indictor of physical

functioning on the aspects of a healthy lifestyle that require it, like

Mirowsky, Ross / EDUCATION AND HEALTH 437

walking and exercising

. The results in the structural model are nearly

the same whether or not these direct effects are specified

. The fit

statistics are a little lower when the three direct effects are fixed to

zero, but still well above the

.900 standard

. On the whole, it appears

that musculoskeletal impairment negatively affects certain aspects of

a healthy lifestyle, but those limitations do not account for the asso-

ciation between lifestyle and health

Discussion

EDUCATION, HUMAN CAPITAL,

LEARNED EFFECTIVENESS, AND HEALTH

The concept of human capital suggests that effective individuals

gain control of their health by developing a healthy lifestyle

. The

model consistently shows results compatible with that hypothesis

. The

aspects of healthy lifestyle form a coherent factor that mediates their

relationship to education, parents' education, and sense of control

. A

healthy lifestyle accounts for most of education's association with

health

. The adult offspring of better educated parents report a healthier

lifestyle than other adults with the same education and economic

status

. A greater sense of control over one's own life accounts for much

of the association between education and healthy lifestyle

The results support the view of education as learned effectiveness

They contradict the view that it marks nothing more than inherited

privilege

. This does not mean that education's effects on income and

economic hardship are irrelevant

. The model indicates that economic

deprivation accounts for some of the association between low educa-

tion and poor health

. It also illustrates education's role in the inheri-

tance of status

. Parents' education increases the respondent's house-

hold income indirectly by raising the respondent's own education but

also directly net of it

. Education is a mark of socioeconomic status and

a mechanism of its inheritance

. But it is also schooling

. As people

learn, they become effective agents

. That effectiveness yields benefits

that include prosperity but also transcend it

. A healthy lifestyle ac-

counts for most of the association between education and health

. This

438

RESEARCH ON AGING

observation supports the view that education enables individuals to

gain control of their lives, including their health 3

ECONOMIC RESOURCES

Income improves health mostly by reducing economic hardship

Income and economic hardship affect health apart from education, and

they mediate a small amount of education's effect on health

. Prosperity

and health go together for reasons beyond their common origin in

learned effectiveness

. Education may protect health mostly by pro-

moting a healthy lifestyle, but that does not make poverty irrelevant

to health

. The large majority of Americans enjoy a level of prosperity

that insulates them from the injuries of poverty

. Below the 20th

percentile, health problems decline sharply with rising levels of in-

come, but above the 20th percentile, additional income has little effect

(Mirowsky and Hu 1996)

. Our results indicate that economic hardship

accounts for most of the negative effect of low household income on

health (low personal control and support account for the rest)

. In

generally prosperous circumstances, lifestyle becomes a dominant

factor in health because most people have adequate incomes

. That fact

does not invalidate the damaging effects of privation for the individu-

als who suffer it

SOCIAL SUPPORT

Social support has no direct effect on healthy lifestyle or on health

adjusting for the sense of control . However, it has a substantial positive

correlation with the sense of control

. Our model treats that as an

unanalyzed correlation (because we did not want to assume a causal

order between the two), but there are reasons to think that some of it

results from a generally positive effect of social support on the sense

of control . Krause (1987) found a parabolic effect of social support on

subsequent change in the sense of control among seniors

. The effect

is positive up to about half a standard deviation above the mean level

of social support

. Thus, social support may usually improve health by

helping people manage their lives more effectively

. On the other hand,

an unusually high level of social support may undermine the sense of

control and thus weaken commitment to a healthy lifestyle

Mirowsky, Ross / EDUCATION AND HEALTH 439

AGE

Age is negatively associated with a healthy lifestyle, which ac-

counts for most of the negative association between age and health

The model shows no direct effect of age on health

. Thus, it implies

that older persons who frequently walk and exercise, remain trim,

drink moderately, and refrain from smoking feel as healthy

and

functional as younger persons with the same lifestyle

. This does not

contradict the fact that the risk of death increases with age even for

those who remain fit

. Rather, it suggests that individuals can feel

healthy and able in old age, delaying and compressing the period of

morbidity and disability (Fries, Green, and Levine 1989

; Rowe and

Kahn 1987)

. It is not clear how much of age's negative effect on health

lifestyle reflects a deterioration over the lifetime and

how much

represents a trend toward a healthier lifestyle in younger generations

The concept of human capital suggests that a lifestyle trend should

account for part of it

. Indeed, successive generations may be increas-

ingly proficient at maintaining a healthy lifestyle as they age because

each successive generation has a higher level of education

. If so, the

research 10 or 20 years from now should find stronger correlations

among the elements of a healthy lifestyle

. In terms of the model, that

would mean larger standardized effects of the lifestyle factor on its

indicators

CA USAL-ORDER AND REPORTING ISSUES

The cross-sectional analyses consistently support the human capital

hypotheses

. They give us no reason to reject the specific hypotheses,

but that is not the same as proving those hypotheses

. The causal-order

assumptions of the model seem reasonable, and they embody the ideas

being tested . However, they probably overstate the unidirectionality

of some effects

. Our model addresses the feedback effect of musculo-

skeletal impairment on walking, exercise, and being overweight

. The

model does not address some other possible feedback effects

. There

is evidence that a self-amplifying dynamic feedback concentrates low

income, economic hardship, and physical impairment together over

time (Mirowsky and Hu 1996)

. Incorporating it in the model would

not undermine any of the evidence that supports a coalescent healthy

lifestyle, family human capital's effects on lifestyle and health, or the

440

RESEARCH ON AGING

importance of personal control in mediating relationships between

education, lifestyle, and health

. It also seems reasonable that impair-

ment and poor health might reduce the sense of control, and that a

long-standing sense of control might have affected educational attain-

ment

. It will take follow-up data to rule out the possibility that cause

flows entirely from health to the sense of control and education rather

than from them to health

. Nevertheless, it seems more likely that a

panel analysis will show self-amplifying feedback between health and

the sense of control (Rodin 1986a, 1986b), and between education and

the sense of control (Andrisani 1978)

. Reciprocal effects would not

undermine the argument that the development of human capital im-

proves health

. Rather, it would show how human capital compounds

with time, partly by preserving the health that sustains effectiveness

Could education's positive effect on health be due to measurement

or reporting bias? In our model, we measure health with a general

assessment of overall health and with reported physical impairments

in mobility and daily activities and sensory impairments in hearing

and seeing

. These are the accepted health measures in surveys

. They

are valid, reliable, and together capture subjective physical well-being

and more objective difficulties in physical functioning

. We adjust for

the tendency to agree with statements regardless of content in the

model, but we do not adjust for the tendency to give socially desirable

responses

. Maybe the well educated simply report healthier lifestyles,

higher personal control, and better health because these are normative

responses

. This seems unlikely, however, since research finds that the

well educated are

less

likely than the poorly educated to give socially

desirable responses (Ross and Mirowsky 1984)

. Furthermore, mortal-

ity studies, which are unaffected by self-reports, show large negative

effects of education on death (Kitagawa and Hauser 1973)

CONCLUSION

Higher educational attainment is associated with better health,

measured as better self-reported health and physical functioning

. A

large part of the reason why the well educated experience good health

is that they engage in a lifestyle that includes walking, exercising,

drinking moderately, avoiding being overweight and not smoking

High levels of personal control among the well educated account for

Mirowsky, Ross / EDUCATION AND HEALTH 441

much of the reason they engage in a healthy lifestyle

. Well-educated

parents further supply their children with resources that include

healthy habits

The well educated also tend to avoid poverty and the strains of

economic hardship that erode health

. Education decreases economic

hardship by way of increasing household income, and at the same

income level the better educated have less trouble paying the bills and

paying for household food, shelter, and clothing than do the poorly

educated

. Under conditions of general prosperity, lifestyle has the

dominant effect on health ; however, that does not minimize the

damaging effects of economic hardship for those who suffer it

"Structured disadvantage" and "individual responsibility" are often

considered rival explanations of health

. Researchers who see health

as a function of a social structure that allocates resources unequally

(Crawford 1986) sometimes criticize the view that health is deter-

mined by lifestyle characteristics such as exercise and smoking

(Knowles 1977)

. In our theory of learned effectiveness, a low sense

of personal control, smoking, being overweight, and a sedentary

lifestyle are not explanatory alternatives to structural disadvantage

. A

low sense of personal control and an unhealthy lifestyle form the

mechanism of structural disadvantage connecting low education to

poor health

Education-based resources go beyond good jobs that provide high

incomes to a sense of personal control and a lifestyle that protects and

fosters health

. Education makes individuals more effective agents in

their own lives . We find a structure of covariances consistent with the

idea that education improves health by enabling individuals to assem-

ble a healthy lifestyle, that a sense of personal agency encourages a

healthy lifestyle and accounts for a large part of education's associa-

tion with healthy lifestyle and with health, and that better educated

parents transmit a healthier lifestyle to their offspring

POLICY IMPLICATIONS

Educational attainment is a root cause of good health (House et al

1994)

. Education gives people the resources to control and shape their

own lives in a way that protects and fosters health

. Apart from benefits

to their own health, well-educated parents transmit resources to their

442

RESEARCH ON AGING

children, including habits such as walking regularly and not smoking,

which ultimately improve adult health status

. Yet, health policymakers

typically do not view improved access to education as a way to

improve the health of the American population

. Instead, they usually

view improved access to medical care as the way to decrease inequal-

ity in health (Davis and Rowland 1983), even though countries with

universal access to medical care have large social inequalities in health

(Hollingsworth 1981

; Marmot et al

. 1987)

. Perhaps policymakers

should invest in educators and schools, not just doctors and hospitals,

for better health

. Unfortunately, money for health (which goes to

hospitals, physicians, pharmaceutical companies, and so on) often

competes directly with money for schools, especially at the state level

In addition to the obvious benefits of education to knowledge, skills,

jobs, wages, economic well-being, and living conditions, broadening

educational opportunities for all Americans could also improve health

NOTES

. Physical capital has value only if people use it productively

A machine is a meaningless

object until someone decides to use it and knows how

. Likewise,

knowledge about health is

meaningless until someone decides to use it and knows how

. There

is no information without

intention

. This is why Schultz (1962) and Becker (1962)

view migration rates as

aggregate

measures of human capital

. To them, migration implies the intentional use of ideas about distant

job markets

. Research that measures socioeconomic status as occupational prestige, status, or rank,

typically excludes people who are not employed

. By one estimate, 42% of British women ages

16 to 64 were excluded from British studies of health and

social class (operationalized

occupational rank) because they had no "occupation" (Carstairs

and Morris 1989)

. We include

persons who are not in the paid economy

. Stratification research typically focuses on occupation

as the important aspect of socioeconomic status

. Yet, we argue, in studying people with paid

jobs, this research eliminates the most disadvantaged from their purview

The exclusion of people

not employed for pay severely truncates variation in socioeconomic

status and attenuates the

effects of educational and economic inequality on health

People who have been fired or laid

off, those engaged in unpaid domestic labor, the nonemployed older persons,

and so on are likely

the most disadvantaged . Many of these people are women

: Almost all homemakers

are women,

and because women live longer than men, the majority

nonemployed older persons are

women

. Finally, when all three indicators of socioeconomic status are included in predictions of

health and mortality, education has the largest effect, followed by income

; occupational status

is typically insignificant (Kitagawa and Hauser 1973 ; Williams

1990

; Winkleby et al

. 1992)

Thus, the advantages of including nonemployed persons likely outweigh any benefit of including

a measure of occupational status

Mirowsky, Ross / EDUCATION AND HEALTH

443

. We ran several alternative specifications of the Covariance Structure (CS) model using

regression analyses

. First, education's positive effects on personal control and health lifestyle

imply that education is not simply a credential

. Using ordinary least squares (OLS) regression,

we further specified a dummy variable comparing people with a college degree or higher to those

without a college degree

. Having a college degree had no independent effect on health, health

lifestyle, or control, over and above years of schooling

. Using OLS regression, we further

specified a nonlinear effect of education on health and found no leveling off of education's

positive effect on health at high levels of education

Second, education correlates positively with all lifestyle characteristics that improve health

Other sociodemographic characteristics are somewhat less consistent

. For example, compared

with younger people, older people have a less healthy lifestyle overall, but they are less likely

to smoke at any given level of health lifestyle (see Table 2)

. Education has no countervailing

negative effect on any of the lifestyle indicators over and above the factor (its effect on moderate

drinking shown in Table 2 is positive)

. OLS and logistic regression analyses reinforce the CS

result that education significantly affects all lifestyle indicators

: It decreases the odds of smoking,

increases the odds of drinking moderately, increases the likelihood of walking and exercising,

and decreases the probability of being overweight (adjusting for parental education, age, gender,

income, and hardship)

. In turn, each aspect of lifestyle has significant independent effects on

health, adjusting for the other indicators and all other variables

. Smoking and being overweight

significantly worsen health

(b =

.165,

t =

.994 and

b = -

.030,

t =

-8

.229, respectively),

moderate drinking, walking, and exercising significantly improve health

(b =

.167, t =

.738,

.022,

t =

.545 and

b =

024,

t =

.860, respectively)

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John Mirowsky is professor of sociology at Ohio State University and editor of the

Journal of Health and Social Behavior

He studies the effects of mastery and equity

on emotional well-being and physical health

. He is coauthor with Catherine E

. Ross

Social Causes of Psychological Distress

(Aldine de Gruyter)

. His recent publica-

tions include "Fundamental Analysis in Research on Well-Being

: Distress and the

Sense of Control" with Catherine Ross in

The Gerontologist (1996), "Physical

Impairment and the Diminishing Effects of Income" with Paul Hu in

Social Forces

(1996),

and "Age, Subjective Life Expectancy, and the Sense of Control

: The Horizon

Hypothesis,

in the

Journal of Gerontology

: Social Sciences

(1997)

He and Cather-

ine Ross are conducting a 3-year follow-up survey of

American adults funded by the

National Institute on Aging

. The project, titled "Aging, Status and the Sense of

Control,

examines the links between physiological aging, age-related changes in

social and physical activities, and the sense of mastery and control

Mirowsky, Ross / EDUCATION AND HEALTH 449

Catherine E

. Ross is professor of sociology at Ohio State University

. She studies the

effects of neighborhoods, work and family on men's and women's health, mental

health, and the sense of

control versus powerlessness

. Her recent publications include

"The Links Between Education and Health" with Chia-ling

Wu in the

American

Sociological Review (1995),

"Education, Age and the Cumulative Advantage in

Health" with Chia-ling Wu in the

Journal of Health and Social Behavior

(1996),

and

"Economic and Interpersonal Work Rewards

Subjective Utilities of Men's and

Women's Compensation" with John Mirowsky in

Social Forces

(1996)

She is princi-

pal investigator on a grant from the National Institute of

Mental Health, "Community,

Crime and Health, " which examines the ways in which neighborhood affects subjec-

tive well-being (Chet Britt, co-principal investigator)

Education and Geriatric Depression in Vietnam: Investigating Gender Differences Using Path Analysis

Article

Full-text available

Feb 2023
Ageing Int

Geriatric depression is a key public health issue, as it leads to many negative health consequences. This study examines the effects of education on depression of older adults in Vietnam, focusing on gender differences. The study utilizes the 2011 Vietnam Aging Survey. The sample consists of individuals aged 60 years and older (N = 2,789, comprising 1,683 females and 1,106 males). Path analysis is used to analyze the direct and indirect effects of education on depression of older males and females. For the indirect effects, the following three channels are investigated: family resources, economic resources, and health status. Education significantly lowers depression for both genders. Education has both direct and indirect effects on the depression of females, but only indirect effects in the case of males. While several channels through which education affects depression are similar for males and females, there are some differences which reflect gender roles in Vietnam. Policies promoting education and gender equality should be strengthened to improve old-age mental health. Specific policies for different groups of older persons are also needed, such as older persons with ADL difficulty and those living alone, as these groups are more likely to suffer from depression.

Knowledge, attitude, and intention to accept COVID-19 vaccine among patients with chronic diseases in southern Ethiopia: Multi-center study

Article

Jan 2023

THE EFFECTS OF COUNTRIES' INCOME LEVELS ON OBESITY: A PANEL DATA APPROACH

Thesis

Full-text available

Jul 2020

Büşra Kesici

Obesity and the diseases related to it are the reasons of approximately 60% of deaths worldwide and cause great increases at rates of morbidity and mortality of countries. It is observed that the obesity problem showed increase year by year in the whole world. Therefore, the studies made on obesity and its reasons gained importance. This study aims to estimate the effect of income on the obesity disease at adults. In our study, obesity is defined, reasons of its emergence, and its effects on the human health and economies of countries are mentioned. The panel data analysis method was applied by using data of WHO and the World Bank belonging to the term 1975-2016. The analysis was made for four groups separately. The first group is the whole countries, including 189 countries. The others are low, middle, and high income countries. As the dependent variable, the prevalence of obesity in adults taken from WHO was used. The variable of interest of our study is GDP per capita. The urbanization, education, employment in industry, health expenditure data of the World Bank are used as control variables. The appropriate model for this analysis is found to be the fixed effects model with the Driscoll-Kraay robust standard errors for all groups. The results indicate that the income increase showed an effect increasing adult obesity in both the low, middle, and high income countries groups and also the whole countries according to our study.

Reflections on Online Psychotherapy in the Age of COVID-19

Article

Apr 2021

This article offers some reflections on current clinical practice in online psychotherapies in the age of the coronavirus pandemic. Drawing on examples from the authors’ own clinical practices, and informed by relevant literature, the article focuses on the implications of the transition from the consulting room to online cyberspace with regard to five themes: transition, the dynamics of administration, therapeutic space(s), working with unconscious dynamics and processes, and uncertainty in a time of uncertainty. As such the article represents a heuristic self-study, enhanced by the authors who are practitioners, educators, and researchers working as a group, appropriately enough, online.

The knowledge, attitudes, and perceptions toward the Oxford AstraZeneca COVID-19 vaccine amongst Primary Health care workers in North-Central Trinidad

Article

Full-text available

Feb 2023

AimTo determine the effects of knowledge, attitudes, and perceptions of primary care health workers toward receiving the Oxford AstraZeneca vaccine in North Central, Trinidad.MethodsA pretested de novo questionnaire containing forty-eight (48) closed ended questions and one (1) open ended question was used to gather data. Descriptive and inferential statistics were used to analyze the data obtained from the questionnaire. These included percentages, means and standard deviations for the descriptive aspect and the Chi-Square test to examine any significant associations. Analysis of Variance (ANOVA) was used to assess any significant differences in means among several categories and the independent samples t-test for assessing any significant difference in means between two categories.Results273 respondents completed the questionnaire. Most of the participants (72.2%) were female and within the age range 25–36 (56.0%). The mean knowledge score about the AstraZeneca vaccine was 16.28 (SD = 2.28) out of 19 with an overall correct response rate of 79%. 30.4% of participants had a good attitude score and 59.7% had a positive perception toward the AstraZeneca vaccine. There were significant associations between knowledge and marital status (p = 0.001), income level (p = 0.001), education level (p < 0.001), and length of employment (p = 0.041); attitudes and sex (p = 0.01), age (p = 0.04), marital status (p = 0.009), income level (p < 0.001), education level (p = 0.005) and category of staff (p < 0.001); perception and sex (p = 0.002), marital status (p = 0.027), income level (p < 0.001), and category of staff (p < 0.001).Conclusions The main contributors to vaccine hesitancy were inadequate duration of clinical trials and fear of adverse side effects. A significant number of participants (17%) were unwilling to get the vaccine due to lack of information.

Psychological Distress Related to the COVID-19 Pandemic: The Protective Role of Hope

Article

Full-text available

Jan 2023

The COVID-19 outbreak and the worldwide lockdown measures had an impact on the global mental health and psychological well-being of the general population. Several studies attempted to investigate the protective and risk factors for psychological distress related to the pandemic. However, to date, little is known about the role of hope in this context. The aim of this study was to determine the relationship between hope and psychological distress related to the COVID-19 outbreak in the general population. The sample consisted of 504 Pakistani people who completed cross-sectionally the COVID-19 Peritraumatic Distress Index (CPDI) and the Adult Hope Scale (AHS). Bivariate Pearson correlation analysis was run to measure the relationship between hope and psychological distress; hierarchical regression analysis was run to investigate the association between demographics and hope with psychological distress. Higher levels of hope predicted lower levels of psychological distress. Being female, being older, lower level of education, urban residence, being married and living in nuclear family systems were associated with higher levels of psychological distress. The study highlights the protective role of hope on psychological distress related to COVID-19, contributing to knowledge on factors promoting positive mental health during emergency times and providing useful information for implementing effective public health policies and programmes.

Decreasing per capita human capital growth in 166 countries from 1990 to 2020

Preprint

Full-text available

Feb 2023

Human capital is widely acknowledged as an inclusive resource that encompasses the knowledge and expertise of citizens, which propels economic development. This research integrates education data with demographic, health, and socioeconomic factors to construct a cross-country human capital monetary accounting framework. We evaluate the levels of educational attainment and the total adult population by stage of life expectancy. Subsequently, we assess education returns based on lifetime income and educational attainment. This accounting tracks the level and changes of human capital in 166 countries from 1990 to 2020, providing multiple indicators to measure human capital for sustainability. The primary findings indicate that globally, the growth trajectory of human capital has declined over the past decade, suggesting a threshold for human capital growth under current investment levels. Based on these findings, it is recommended that policymakers consider this shift and align long-term human capital investment with sustainable growth paths.

A perceived control‐relationally devaluing experiences model of low socioeconomic status vulnerability to negative relationship outcomes

Article

Feb 2023

We propose that individuals low (vs. high) in socioeconomic status (SES) are vulnerable to impaired relationship functioning through two different mutually reinforcing paths that both directly implicate perceptions of control and relational devaluation. The first of these involves chronic exposure to relational devaluation as a function of factors such as stigmatization in broader society that serves to undermine low SES individuals’ perceptions of control. The second involves enhanced reactivity to relationally devaluing experiences such as discrimination and ostracism as a function of this limited reserve of perceived control. We present a perceived control‐relationally devaluing experiences model of low SES vulnerability to impaired relationship functioning that incorporates these predictions and further specifies how low SES individuals’ reduced perceptions of control may help account for documented associations between low SES and negative interpersonal outcomes such as hostility, aggression, and reduced relationship quality. We conclude by considering implications for intervention as well as potential alternative and complementary mechanisms.

Conditions facilitating aging in place in rural communities: The case of smart senior towns in Iowa

Article

Jan 2023
J RURAL STUD

Relations between clinical characteristics and cognitive deficits among adult patients diagnosed with major depressive disorder

Article

Nov 2022

Objective: The present study examined the relations between clinical characteristics and cognitive deficits in adult patients with major depressive disorder (MDD) from a local outpatient psychiatric clinic in Malaysia. Methods: The present sample included 110 participants aged 20-60 years old. Participants were invited to provide their information on sociodemographic variables (age, gender, and educational level) and clinical characteristics (age at onset of depression and duration of illness) and to complete a series of cognitive performance measures including the Trail Making Tests A (psychomotor speed) and B (executive function), the Digit Symbol Substitution Test (attention), and the Auditory Verbal Learning Test (immediate free recall, acquisition phase, and delayed recall). The Mini International Neuropsychiatric Interview Version 6.0 was used to confirm the diagnosis of MDD and the Montgomery-Åsberg Depression Rating Scale was used to assess illness severity. Results: At the bivariate level, relations of age and educational level to all cognitive deficit domains were significant. At the multivariate level, only educational level and illness severity consistently and significantly predicted all cognitive deficits domains. Conclusions: Therapeutic modalities should be individualised whilst considering the impacts of cognitive deficits in an attempt to prevent further deterioration in psychosocial functioning of MDD patients.KEY POINTSCognitive deficits are an elemental component of Major Depressive Disorder (MDD) persisting during a current major depressive episode or during remission, altering individuals' ability to process information and changes the way they perceive and interact with the environment.Cognitive deficits in MDD are evident among the upper-middle income groups in South-Eastern Asian countries warranting more local research as such deficits could lead to functional decline and work performance such as absenteeism and presenteeism.Therapeutic modalities should be individualised by taking the impacts of cognitive deficits into consideration to promote psychosocial functioning of MDD patients.

Eliminating Defense and Agreement Bias from Measures of the Sense of Control: A 2 X 2 Index

Article

Full-text available

Jun 1991
SOC PSYCHOL QUART

Defensiveness and a tendency to agree bias findings based on unbalanced measures of the sense of control. A comprehensive model shows the defense bias introduced by not balancing the number of statements about good and bad outcomes and the agreement bias introduced by not balancing the number of internal (instrumental) and external (fatalistic) statements. Notably, indexes that are composed only of external statements have spuriously larger variances, reliabilities, and correlations than do those that are composed solely of internal statements. Thus study develops and evaluates a balanced 2 X 2 measure of the sense of control over one's own life. The measure has three properties: (1) it is not biased by self-defense and self-blame or by the tendency to agree with statements regardless of content; (2) it has construct validity for community survey research on income, education, minority status, aging, or well-being; and (3) its form and length are suitable for community surveys. The index is validated using data from 225 students and from 713 residents of Illinois.

Leisure-time physical activity levels and risk of coronary heart disease and death. The Multiple Risk Factor Intervention Trial

Article

Nov 1987

Arthur Leon

Households, Employment, and the Sense of Control

Article

Sep 1992
SOC PSYCHOL QUART

This paper investigates how the combination of job and household circumstances modifies the association between employment and the sense of control over one's life. Data are from a 1985 sample of 809 Illinois adults. The average sense of control is greater among people with paying jobs than among those without. The difference increases with greater job autonomy and higher earnings. Not all household contexts of employment are alike, however; people who do most of the household work find employment less beneficial to their sense of control. Also, the more family income comes from sources other than one's earnings, the less that employment increases the sense of control. For married women, the typical combination of low pay, low autonomy, high responsibility for household chores, and family income other than personal earnings negates the positive association between employment and the sense of control.

How College Affects Students

Article

May 1992

Leisure-Time Physical Activity Levels and Risk of Coronary Heart Disease and Death

Article

Nov 1987

Arthur Leon

The relation of self-selected leisure-time physical activity (LTPA) to first major coronary heart disease (CHD) events and overall mortality was studied in 12 138 middle-aged men participating in the Multiple Risk Factor Intervention Trial. Total LTPA over the preceding year was quantitated in mean minutes per day at baseline by questionnaire, with subjects classified into tertiles (low, moderate, and high) based on LTPA distribution. During seven years of follow-up, moderate LTPA was associated with 63% as many fatal CHD events and sudden deaths, and 70% as many total deaths as low LTPA (P<.01). Mortality rates with high LTPA were similar to those in moderate LTPA; however, combined fatal and nonfatal major CHD events were 20% lower with high as compared with low LTPA (P<.05). These risk differentials persisted after statistical adjustments for possible confounding variables, including other baseline risk factors and Multiple Risk Factor Intervention Trial group assignments. It is concluded that LTPA has a modest inverse relation to CHD and overall mortality in middle-aged men at high risk for CHD. (JAMA 1987;258:2388-2395)

Physical Impairment and the Diminishing Effects of Income

Article

Mar 1996

The effect of income on physical impairment steepens at lower levels of income. Why? Two national surveys show the following. Basic needs: the level of impairment and its rate of increase rise sharply as household income drops below the 20th percentile; above that level greater income has little effect; economic hardship explains much of the pattern. Resource substitution: education reduces the association between impairment and low income, but low education often coincides with low income. Compounding problems: impairment suppresses the rise of income, concentrating economic and health problems over time. Status lifestyle: Exercise increases with income but explains little of the association with impairment. Social background: stable traits that affect both income and impairment account for about half of their association, with education the largest factor.

The Links Between Education and Health

Article

Oct 1995
AM SOCIOL REV

The positive association between education and health is well established, but explanations for this association are not. Our explanations fall into three categories: (1) work and economic conditions, (2) social-psychological resources, and (3) health lifestyle. We replicate analyses with two samples, cross-sectionally and over time, using two health measures (self-reported health and physical functioning). The first data set comes from a national probability sample of U.S. households in which respondents were interviewed by telephone in 1990 (2,031 respondents, ages 18 to 90). The second data set comes from a national probability sample of U.S. households in which respondents ages 20 to 64 were interviewed by telephone first in 1979 (3,025 respondents), and then again in 1980 (2,436 respondents). Results demonstrate a positive association between education and health and help explain why the association exists. (1) Compared to the poorly educated, well educated respondents are less likely to be unemployed, are more likely to work full-time, to have fulfilling, subjectively rewarding jobs, high incomes, and low economic hardship. Full-time work, fulfilling work, high income, and low economic hardship in turn significantly improve health in all analyses. (2) The well educated report a greater sense of control over their lives and their health, and they have higher levels of social support. The sense of control, and to a lesser extent support, are associated with good health. (3) The well educated are less likely to smoke, are more likely to exercise, to get health check-ups, and to drink moderately, all of which, except check-ups, are associated with good health. We conclude that high educational attainment improves health directly, and it improves health indirectly through work and economic conditions, social-psychological resources, and health lifestyle.

Alienation Motifs in Contemporary Theorizing: The Hidden Continuity of the Classic Themes

Article

Sep 1983
SOC PSYCHOL QUART

Melvin Seeman

This analysis is not another lament about the unclarity of the concept of alienation, nor a proposal for new conceptual distinctions. Noting the rediscovery of alienation in the 1950s, and its political-practical and intellectual-analytical prominence in the 1960s, the question is raised: Is the idea of alienation now (like "cognitive dissonance" and "authoritarianism"" in psychology) an unfashionable has-been whose analytical utility has been found wanting? On the contrary, an argument is developed for the view that contemporry theorizing finds the classical dimensions (if not the name) of alienation essential in both micro-and macroanalayses. The documentation of this argument involves examples from widely varying perspectives (e.g., Marxists; learning theorists; symbolic interactionsits), dealing with widely varying domains of experience (e.g., health, work, and collective behavior), employing the several varieties of alienation (powerlessness, meaninglessness, sense of social isolation vs. community, etc.) The significance of this continued prominence of alienation (or alienation-like) constructs, in both psychology and sociology, is assessed.

Education's Lasting Influence on Values

Article

Mar 1981

Sociomonetary patterns and specifications

Article

Dec 1990

Michael Epelbaum

Sociomonetary relationships (A) endow money with meaning, significance, and identity, (B) are obfuscated by original monetary values, and (C) can be captured by specified monetary values (i.e., monetary values in specified sociomonetary functions). Moreover, the validity and reliability of monetary data depend upon identification and specification of sociomonetary functions. Consequently, it is necessary to examine which forms of sociomonetary functions best conform to criteria of specification. For example, are these criteria optimized by simple and parsimonious monomial power functions (which provide a basis for the formulation of a power law of sociomonetary functions)? Such questions can be answered with the aid of explorations of sociomonetary relationships. My exploration reveals four prevalent and interrelated (but not universal nor permanent) patterns of sociomonetary relationships in synchronic and diachronic analyses of demographic, survey, and experimental data. These patterns are characterized by r-shaped or L-shaped curves in sociomonetary scatter plots for a response to money, and J-shaped or L-shaped curves in sociomonetary scatter plots for a monetary response. These sociomonetary patterns appear to be linked to (A) similar patterns among nonmonetary phenomena, (B) processes of legitimation, violence, and inequality, and

Education, Personal Control, Lifestyle and Health: A Human Capital Hypothesis

Abstract and Figures

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