Published by Oxford University Press on behalf of the International Epidemiological Association
ß The Author 2011; all rights reserved. Advance Access publication 15 February 2011
International Journal of Epidemiology 2011;40:786–793
doi:10.1093/ije/dyr011
OTHER ORIGINAL ARTICLES
Explaining low mortality among US immigrants
relative to native-born Americans: the role
of smoking
Laura Blue1* and Andrew Fenelon2
1
Office of Population Research, Princeton University, Princeton, NJ, USA and 2Department of Sociology and Population Studies
Center, University of Pennsylvania, Philadelphia, PA, USA
*Corresponding author. Office of Population Research, Wallace Hall (Floor 2), Princeton University, Princeton, NJ 08544, USA.
E-mail: [email protected]
Accepted
11 January 2011
Background In many developed countries, immigrants live longer—that is, have
lower death rates at most or all ages—than native-born residents.
This article tests whether different levels of smoking-related mortality can explain part of the ‘healthy immigrant effect’ in the USA,
as well as part of the related ‘Hispanic paradox’: the tendency for
US Hispanics to outlive non-Hispanic Whites.
Methods
With data from vital statistics and the national census, we calculate
lung cancer death rates in 2000 for four US subpopulations:
foreign-born, native-born, Hispanic and non-Hispanic White. We
then use three different methods—the Peto–Lopez method, the
Preston–Glei–Wilmoth method and a novel method developed in
this article—to generate three alternative estimates of smokingrelated mortality for each of the four subpopulations, extrapolating
from lung cancer death rates. We then measure the contribution of
smoking-related mortality to disparities in all-cause mortality.
Results
Taking estimates from any of the three methods, we find that
smoking explains 450% of the difference in life expectancy at
50 years between foreign- and native-born men, and 470% of the
difference between foreign- and native-born women; smoking explains 475% of the difference in life expectancy at 50 years between
US Hispanic and non-Hispanic White men, and close to 75% of the
Hispanic advantage among women.
Conclusions Low smoking-related mortality was the main reason for immigrants’ and Hispanics’ longevity advantage in the USA in 2000.
Keywords
Health status disparities, minority health, smoking, lung neoplasms,
mortality, statistics as topic
Introduction
In many developed countries, including Australia,1
Canada,2 Germany3 and the USA,4 immigrants appear
to outlive native-born residents, with lower death
rates at most or all ages. Scholars have been puzzled
by this ‘healthy immigrant’ (or ‘healthy migrant’)
effect—sometimes also called the ‘immigrant paradox’—as it runs counter to an otherwise persistent
trend for richer and better-educated populations to
786
ROLE OF SMOKING IN LOW MORTALITY AMONG US IMMIGRANTS
live longer. In the USA, for example, immigrants are
not only less well educated, less wealthy and more
likely to live in poverty,5 but also often have poorer
access to health care. For similar reasons, scholars
have been perplexed by the ‘Hispanic paradox’: a tendency for US Hispanics to live longer6 and healthier
lives than non-Hispanic Whites.
There are several hypotheses to explain immigrants’
life expectancy advantage. Kennedy et al.7 found evidence for migrant self-selection—that people who are
relatively healthy find it easier to settle in new countries. There is also some evidence for selection in
return migration—a so-called ‘salmon bias’ effect,
where unhealthy migrants are more likely than
healthy ones to return to their countries of origin,8
although Turra and Elo9 suggest this can explain
only some fraction of migrants’ and Hispanics’ longevity advantage in the USA. Finally, immigrants may
maintain healthier lifestyles in their host country
than native-born residents. A study of adolescent behaviour10 shows that California minority immigrants,
for example, eat more fruit and vegetables and drink
less soda than the state’s non-Hispanic White adolescent population. Foreign-born adults in the USA also
have lower rates of obesity than native-born
Americans.11
We suggest that smoking habits may contribute to immigrants’ relative good health, at least in the USA.
Immigrants and Hispanics are less likely to be current
smokers12,13 or former smokers13 than native-born US
Whites. Although the differences in smoking prevalence
are only 2 percentage points among men and 6
among women, smoking-attributable mortality is affected not only by current behaviour, but also by past
behaviour. People dying of smoking-related diseases
today—almost always people in middle age or older—
most likely began smoking as teenagers or young adults
in the 1950s through 1970s, a period of relatively heavy
tobacco use in the USA. Figures from the National
Center for Health Statistics (NCHS) put smoking prevalence in the mid-1960s at 51% among adult men and
33% among adult women.14
Using individual-level data, Denney et al.15 show
that Hispanics’ survival advantage is attenuated once
controls for smoking status are introduced. However,
such studies may still fail to capture the full impact of
smoking if—as reports from the National Health
Interview Survey suggest13—Hispanic smokers are
typically lighter smokers than other smokers are.
Indirect methods may yield more robust estimates of
smoking-attributable mortality.
Methods
We estimate the contribution of smoking-attributable
mortality to all-cause mortality disparities observed in
2000 between foreign-born US residents and nativeborn Americans, and between US Hispanics and nonHispanic Whites.
787
We use three different methods to generate, for each
analysis, three alternative estimates of smokingattributable mortality. All three methods use the
death rate from lung cancer as a marker of accumulated smoking exposure within a population. This approach is supported by a large research literature that
shows smoking to be the main source of variation in
lung cancer mortality among populations.16–18 Our
three methods are the Peto–Lopez method,19,20
which extrapolates smoking-related mortality from
lung cancer mortality based on risks observed
among smokers in the Cancer Prevention Study II;
the newer Preston–Glei–Wilmoth (PGW) method,21
which instead extrapolates smoking-related deaths
from correlations between lung cancer mortality and
mortality from other causes across 20 high-income
countries; and a novel indirect estimation technique,
outlined below. While all three methods make broadly
similar assumptions, they allow assumptions to be
relaxed in different ways.
Calculation of lung cancer mortality
For all three methods, we first calculated all-cause
mortality for the year 2000, tabulating age-specific
death rates by sex for four subpopulations: foreignborn, native-born, Hispanic and non-Hispanic White
(Figure 1). We took rate numerators (deaths) from
the Multiple Cause-of-Death Public-Use Microdata
files, available from NCHS. These data include decedents’ race, ethnicity and place of birth, as recorded
on each person’s death certificate. From a total of
2 407 193 deaths in 2000, we dropped 363 entries
without a recorded age and 14 378 with missing
place of birth. We followed the death certificate classification of ‘Hispanic’ and ‘non-Hispanic White’. We
considered anyone born outside the 50 US states and
the District of Columbia to be ‘foreign-born’, and
anyone born inside to be ‘native-born’. We took our
rate denominators (population counts) from the US
2000 Census 5% Public Use Microdata Sample Files.
These data, too, provide individual-level records on
race, ethnicity and place of birth. Using these same
data sources, we then calculated age- and sex-specific
death rates in 2000 for lung cancer only, using as our
numerator the number of deaths indicated on death
certificates
as
attributable
to
lung
cancer
[International Classification of Diseases (ICD)-10
codes C33–C34].
A new method to estimate
smoking-attributable mortality
We have developed a new method to estimate smoking-attributable mortality. Our method builds on the
familiar assumption that lung cancer mortality is a
reliable marker of smoking exposure in a population.
Not all lung cancers are caused by smoking, and lung
cancer is not the only deadly smoking-related condition. However, if we know both the proportion of
lung cancers caused by smoking (P) and the
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
Death rate
1
Females: native vs foreign born
0.1
0.01
0.001
Males: native vs foreign born
1
Death rate
788
0.1
0.01
0.001
50
55
60
65 70
Age
Native
75
80 85+
Foreign
50
55
60
Native
65 70
Age
75
80 85+
Foreign
Figure 1 US death rates (log scale) in 2000
proportion of smoking-related mortality that is lung
cancer mortality (Q), we can estimate total smoking
deaths (DS) as follows:
DS ¼
P DL
Q
where DL is the number of lung cancer deaths.
A great deal of epidemiological work has focused on
the two proportions that we call here P and Q. P is
simply the attributable risk, the proportion of lung
cancer mortality that would not have occurred in
the absence of smoking:
ðML ML Þ
P¼
ML
where ML is the observed population lung cancer
death rate, and ML is the lung cancer death rate
among members of that population who have never
smoked. It can be difficult to get precise ML values by
age and sex, since lung cancer deaths are rare among
never-smokers. However, Michael Thun et al.22 have
recently produced such estimates, pooling together
rates from both US Cancer Prevention Studies, the
Nurses’ Health Study, the Women’s Health Study
and other major US and non-US trials and cohort
studies. We use the pooled estimates among neversmoker Whites (both in the USA and abroad) as
our baseline risk for lung cancer mortality in the
absence of smoking. We then calculate P by age and
sex for each subpopulation (see Supplementary
Appendix A for values, available as supplementary
data at IJE online).
We calculate Q from Centers for Disease Control and
Prevention (CDC) tabulations of smoking-related
mortality from 1997 to 2001.23 During those years,
the CDC estimates that lung cancer caused 32% of
all smoking-attributable deaths among men and
29% among women, with the bulk of deaths due to
other conditions, including heart disease, chronic obstructive pulmonary disease and cancer of other
organs. In our calculations, therefore, we take Q as
0.32 for men and 0.29 for women. For simplicity,
we assume these values do not vary by age.
Sensitivity analyses
The Peto–Lopez and PGW methods assume that
excess lung cancer deaths and other smokingattributable deaths are related in the same way in
all populations. Our new method allows this assumption to be relaxed. To test robustness, we use the new
method to calculate six different scenarios in addition
to our principal estimates.
Low estimate: we allow P and Q to vary by subpopulation. P is calculated as in the principal analysis.
Among native-born Americans and non-Hispanic
Whites Q ¼ 0.29 for females and Q ¼ 0.32 for
males, as observed in the population at large.
Among immigrants and Hispanics, however,
Q ¼ 0.24 for females and Q ¼ 0.27 for males—arbitrarily set values that allow immigrants and
Hispanics to be unusually susceptible to non-lung
cancer smoking deaths.
High estimate: we allow P and Q to vary by subpopulation. P is calculated for native-born
Americans and non-Hispanic Whites as in the principal analysis; for immigrants and Hispanics, it
is calculated from the never-smoker lung cancer
death rates among Asians compiled by Thun et al.22
Among native-born Americans and non-Hispanic
Whites, Q ¼ 0.29 for females and Q ¼ 0.32 for males
as observed in the population at large. Among immigrants and Hispanics, Q ¼ 0.34 for females and
Q ¼ 0.37 for males—arbitrarily set values that allow
immigrants and Hispanics to be unusually resistant
to smoking-related deaths from causes other than
lung cancer.
Salmon bias correction: P and Q are the same as
those from ‘low estimate’. We account here for the
possibility that observed deaths among immigrants
or Hispanics are only some fraction of true deaths,
as sick immigrants may leave the country to die.
ROLE OF SMOKING IN LOW MORTALITY AMONG US IMMIGRANTS
Data from the Surveillance, Epidemiology and End
Results (SEER) Program24 show that the ratio of
lung cancer mortality to lung cancer incidence is
higher for non-Hispanics (0.90 for men; 0.76 for
women) than for Hispanics (0.79 for men; 0.57
for women). This could be a sign of Hispanics’ selective migration, or it could be that Hispanics have
lower case severity (perhaps because they smoke
less). Here, we assume the former, and inflate lung
cancer death rates for immigrants and Hispanics
by the full difference in mortality-to-incidence, multiplying by 1.14 for men and by 1.34 for women. [Data
on mortality-to-incidence exist only by ethnicity,
and not by place of birth. The mortality-to-incidence
ratio is 14% higher for non-Hispanic men than
Hispanic men (0.90/0.79 ¼ 1.14) and 34% higher for
non-Hispanic women relative to Hispanic women
(0.76/0.57 ¼ 1.34).]
½ Salmon bias correction: P and Q are those from
‘low estimate’. Lung cancer death rates among immigrants and Hispanics are inflated by one-half of
the difference in SEER mortality-to-incidence ratios
observed between Hispanics and non-Hispanic
Whites. For foreign-born and Hispanic women,
lung cancer death rates are inflated by multiplying
by 0.5*(0.76/0.57 1) þ 1 ¼ 1.16; for men, by
0.5*(0.90/0.79 1) þ 1 ¼ 1.07.
Age-varying Q: we allow the proportion of smokingattributable deaths caused by lung cancer to vary by
age. We use the PGW method21 and national data
for the USA in 2000 (described above) to calculate
new estimates of Q, by sex, for each 5-year age
group.
Strong adjustment for possible confounding: taking
Q from the CDC assumes that all estimated excess
deaths among smokers are directly caused by smoking.
Here, we assume only half of smokers’ excess non-lung
cancer deaths are smoking-attributable. That is,
Q ¼ 0.29/(0.29 þ [1 0.29]*0.5) ¼ 0.45 for women
and Q ¼ 0.32/(0.32 þ [1 – 0.32]*0.5) ¼ 0.48 for men.
Results
In 2000, native-born Americans had substantially
higher lung cancer death rates than US immigrants,
and non-Hispanic Whites had substantially higher
rates than US Hispanics (Figure 2). Using three alternative methods, we estimate, as a result, that total
smoking-related mortality was also higher among
native-born Americans and non-Hispanic Whites
than among US immigrants and Hispanics. For each
method, we present detailed mortality estimates by
age and sex in Supplementary Appendix B (available
as supplementary data at IJE online).
Males: native vs foreign born
1
Lung cancer death rate
Lung cancer death rate
Females: native vs foreign born
1
0.1
0.01
0.001
0.0001
0.1
0.01
0.001
0.0001
50
55
60
65 70
Age
Native
75
80 85+
50
Foreign
Females: non-Hispanic vs Hispanic
60
65 70
Age
75
80 85+
Foreign
Males: non-Hispanic vs Hispanic
1
1
Lung cancer death rate
Lung cancer death rate
55
Native
0.1
0.01
0.001
0.0001
0.1
0.01
0.001
0.0001
50
55
60
65 70
Age
Non-Hispanic White
75
80 85+
Hispanic
Figure 2 US lung cancer death rates (log scale) in 2000
789
50
55
60
65
70
Age
Non-Hispanic White
75
80 85+
Hispanic
790
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
We use Arriaga’s method25 to decompose differences
in life expectancy at age 50 years into two components: a component due to smoking and a component
due to other factors. Taking estimates from any of the
three methods, we find that smoking accounts for at
least 50% of migrants’ advantage in life expectancy at
50 years among men and at least 70% among women.
Smoking explains 475% of the difference in life expectancy at 50 years between US Hispanic and
non-Hispanic-White men, and close to 75% of this
difference among women (Figure 3).
Table 1 shows sensitivity-analysis results. In most of
the scenarios, smoking still accounts for 450% of the
differences in life expectancy at 50 years. In one instance, smoking is estimated to explain 4100%; this
means that, in the absence of smoking, male life expectancy would be higher among non-Hispanic
Whites than among Hispanics.
Discussion
We find that low mortality from smoking is the main
reason for immigrants’ and Hispanics’ longevity advantage in the USA in 2000. While previous studies
have documented lower smoking prevalence among
US
immigrants
compared
with
native-born
Americans, and among Hispanics compared with
non-Hispanic Whites, to our knowledge none of
Foreign born–native born
Females
2.09 years
Life expectancy disparity (years)
3
Males
2.74 years
2.5
2
Other Factors
1.5
Smoking
1
0.5
0
PL
78.0%
PGW
72.2%
BF
71.0%
PL
66.8%
PGW
53.6%
BF
58.3%
Hispanic–non-Hispanic White
Females
2.82 years
Life expectancy disparity (years)
3
Males
2.11 years
2.5
2
Other Factors
1.5
Smoking
1
0.5
0
PL
76.2%
PGW
74.8%
BF
75.3%
PL
77.7%
PGW
87.2%
BF
88.2%
Figure 3 Differences in life expectancy at age 50 years and proportion explained by smoking, by nativity and ethnicity.
PL ¼ Peto–Lopez method; PGW ¼ Preston–Glei–Wilmoth method; BF ¼ Blue–Fenelon method, developed in this article
ROLE OF SMOKING IN LOW MORTALITY AMONG US IMMIGRANTS
791
Table 1 Sensitivity analysis (from the new method to estimate smoking-attributable mortality): proportion of the difference in life expectancy at 50 years explained by smoking
Foreign–native
Scenario
Principal estimate
Hispanic–non-Hispanic White
Females (%)
71.02
Males (%)
58.27
Females (%)
75.33
Males (%)
88.17
Low estimate (P and Q vary by subpopulation)
61.75
47.77
70.75
75.71
High estimate (P and Q vary by subpopulation)
84.90
79.02
84.58
116.56
Low estimate with strong salmon-bias correction
43.84
38.42
61.89
64.61
Low estimate with ½ salmon-bias correction
52.79
43.10
66.32
70.16
Age-varying Q (with Q from PGW)
66.12
46.77
74.98
73.55
Strong adjustment for possible confounders
45.77
38.84
48.55
58.78
these earlier studies calculates the contribution of
smoking to US mortality disparities.
Like other demographers and epidemiologists,19–21,26
we believe lung cancer mortality is the most reliable
marker of a population’s smoking behaviour.
Mortality data are available by age and sex in many
developed countries, whereas detailed data on smoking prevalence, duration and intensity generally are
not. To date, studies using indirect methods have typically found that smoking explains a greater proportion of longevity differences than studies using direct
methods. For example, Jha et al.27 (using the Peto–
Lopez method) found that smoking explains more
than half of the social gradient in mortality in
England and Wales, whereas English longitudinal studies generate estimates closer to one quarter.28,29
Crude survey measurement of smoking habits may
explain part of the discrepancy. Surveys can suffer
from inaccurate self-reports, from non-response rates
that leave the sample of respondents unrepresentative
of the population at large, and—where participants
are followed over time—by unrecorded changes in
smoking behaviour. It is also difficult to measure
smoking intensity with precision; survey respondents
are usually asked to categorize their consumption into
large bins, such as ‘more than 20 cigarettes per day’
or ‘former smoker’.
In this article, we develop a new method to estimate
smoking-attributable deaths. Our technique is similar
to the widely accepted Peto–Lopez method, although
it is somewhat simpler; it ignores age variation in the
cause-of-death distribution. Our main advantage,
however, is the possibility of straightforward sensitivity checks. We can relax assumptions about P and Q,
whereas the Peto–Lopez and PGW methods both
assume that never-smoker lung cancer risks will not
vary across populations (as they may with differences
in genetic susceptibility or in exposure to carcinogens
like asbestos or smoke from cooking fires). In practice, our new estimates of smoking-related mortality
appear quite similar to those generated using existing
methods.
We consider there to be two main sources of uncertainty in our results. First, all three methods used in
this article assume that death certificates (and thus
the NCHS Multiple Cause-of-Death data) contain
complete and correct information on decedents’ birthplace, race, ethnicity and cause of death. As noted
above, very few death records (<1%) are missing
entries for these variables. Our assumption is nonetheless complicated by the fact that race and Hispanic
status are identified differently in the Census (where
they are given by self-report) than they are in death
data (where reports are made by a third party).
However, although race and ethnicity misclassification on death certificates may be more common
among immigrants and Hispanics than among
native-born non-Hispanics,30 Arias et al.31 show that
the magnitude of this bias is probably not great.
Furthermore, we see no obvious reason that these
classification errors should also vary systematically
and greatly by lung cancer as a cause of death. As a
result, errors in birthplace and ethnicity recorded on
death certificates may indeed cause us to overestimate
both the immigrant paradox and the Hispanic paradox, but, crucially, they should not greatly bias our
estimates of the proportion of these disparities that
are caused by smoking—provided that the direction
of the disparities is correct. We are confident that it
is. Cohort study results,32 death data from Social
Security9 and Medicare,30 and new US life tables by
Hispanic origin6 are unlikely to suffer the same misclassification errors. All show a clear Hispanic or immigrant advantage.
Secondly, for the new estimation technique, there is
some uncertainty in estimates of the key inputs, P
and Q. For simplicity, to calculate P, we have assumed
all US subpopulations would have identical lung
cancer death rates in the absence of smoking. We
chose to approximate this rate with the never-smoker
lung cancer death rates of Whites, compiled by Thun
et al.22 Whites have the lowest rates of any of the race
in these authors’ global review. Using White rates
therefore generates the most conservative estimates
of the proportions of the immigrant paradox and
the Hispanic paradox that are due to smoking. If we
assumed instead that immigrants had the baseline
lung cancer risk of either Blacks or Asians in Thun
792
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
et al.’s22 analysis (as we do in the ‘high estimate’ of
the sensitivity analysis), we would estimate that
smoking explains a larger proportion still.
For our estimates of Q, the proportion of smokingrelated deaths that are lung cancer deaths, we import
figures from the CDC. Although we believe these figures are among the best available, they are based on
relative risks observed in cohort studies of smoking.
Past cohorts were rarely representative of the US
population, and it remains almost impossible to control fully for confounders that correlate smoking with
diseases not actually caused by smoking.33
Furthermore, we cannot be certain that the causeof-death distribution of smoking deaths is constant
across subpopulations in which smoking-related mortality has not been studied, and calculations using the
PGW method suggest this distribution does vary by
age, violating the assumption of age-invariant Q. We
consider several possible sources of error in our sensitivity analysis. Ultimately, however, the input figures in these alternative scenarios are to some
degree arbitrary.
As it is unclear which assumptions about smokingrelated mortality may be most accurate, in this article
we have estimated the contribution of smoking to
mortality disparities using three different methods.
In addition, we have conducted sensitivity analysis
for six alternative scenarios, relaxing assumptions
about never-smoker lung cancer mortality, the
cause-of-death distribution of smoking-attributable
deaths, possible confounding and salmon bias. Many
of these scenarios are no doubt highly implausible.
Nevertheless, our estimates of the contribution
of smoking to mortality disparities are very similar
across all three methods, and are only moderately
sensitive to the assumptions changed in the sensitivity analysis. As a result, though one may doubt the
precision of figures we use to estimate smokingrelated mortality, we remain quite confident in our
conclusion: smoking is likely the major cause of
America’s immigrant paradox and the related
Hispanic paradox.
Supplementary Data
Supplementary data are available at IJE online.
Funding
This work was supported by the National Institutes of
Health (5T32 HD 007163 and 5T32 HD 007242–28).
Acknowledgements
We thank Samuel H. Preston and two anonymous
referees for their comments and guidance.
Conflict of interest: None declared.
KEY MESSAGES
In the USA, foreign-born residents have higher life expectancy than native-born Americans, and
Hispanics have higher life expectancy than non-Hispanic Whites, despite socioeconomic disadvantages among the long-lived populations.
We hypothesize that smoking may account for some of these observed life expectancy differences by
nativity and ethnicity.
We use three different indirect methods—the Peto–Lopez method, the Preston–Glei–Wilmoth method
and a novel method outlined in this article—to estimate smoking-related mortality in 2000 for four
US subpopulations: foreign-born, native-born, Hispanic and non-Hispanic White.
Using any of the three indirect estimation techniques, we find that smoking explains more than half
of the difference in life expectancy at 50 years between foreign-born US residents and native-born
Americans, and close to three-quarters of the difference in life expectancy between US Hispanics and
non-Hispanic Whites.
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