The Role of Personal Attributes in the Genesis and Progression of Lung Disease and Cigarette Smoking

Abstract

Objectives. We examined early maladaptive personal attributes (e.g., depression), later lung disease, and later maladaptive personal attributes over a significant part of a woman’s life.

Methods. We gathered longitudinal data on a prospective cohort of community-dwelling women (n = 498) followed from young adulthood to late midlife.

Results. We used structural equation modeling to assess the interrelations of maladaptive personal attributes, cigarette smoking, lung disease, and financial strain. The results supported a mediational model through which early maladaptive personal attributes were associated with smoking (b = 0.17, P < .001), which in turn predicted later lung disease (b = 0.33, P < .001), and lung disease was related to later family financial difficulties (b = 0.09, P < .05), which in turn were associated with later maladaptive personal attributes (b = 0.35, P < .001).

Conclusions. Our results address a number of important public health and clinical issues. An understanding of the interrelations of smoking, underlying mental health conditions, financial stress, and later mental health conditions on the part of physicians and other health care providers can be critical in managing patients with lung disease.

Lung disease remains a major cause of mortality in developed nations as well as developing countries.¹ The role of cigarette smoking in causing lung disease has been widely known since the classic studies of lung cancer by Wynder and Graham² and Doll and Hill.³ Cigarette smoking increases the risk of developing lung cancer.⁴ In addition, cigarette smoking causes nonneoplastic lung diseases, such as emphysema and chronic bronchitis, and increases the risk of dying of chronic bronchitis or emphysema.⁴

In contrast to studies on the relationship of cigarette smoking to lung disease,⁵ few studies involving community samples have focused on the role of maladaptive personal factors (e.g., depression, anxiety) in the development and progression of lung disease. Although the devastating psychological impact of advanced lung disease and the high rate of psychopathology in patients with lung disease have been described in small studies,^6,7 there have been few systematic investigations of the role of maladaptive personal attributes in predicting lung disease and contributing to its progression over several decades (but see Katz et al.⁸ for a longitudinal study involving a community sample). In this study, we assessed psychosocial predictors and concomitants of lung disease among women from young adulthood to late midlife.

With respect to the role of maladaptive personal attributes, there is some evidence that negative emotions and behaviors are related to chronic obstructive pulmonary disease (COPD) and to deterioration in lung function.^9–11 According to Laurin et al.,¹² patients with psychiatric disorders are at greater risk for exacerbations of COPD than are individuals without psychiatric disorders. In a recent study, Katz et al.⁸ reported that the prevalence of depression among individuals with COPD is quite high. One of the possible mediators between maladaptive personal attributes and lung disease is cigarette smoking. Cigarette smoking has been linked to early maladaptive personal attributes, such as depressive symptoms and anxiety,^9,13,14 and to later lung disease.⁴

According to self-medication theory, people smoke to relieve psychological tension.¹⁵ Personal factors, such as a lack of self-control, may also influence a person’s decision to smoke despite knowledge of the harmful consequences of cigarette smoking.^14,16 There is also evidence that lung disease is related to family financial distress^17,18 and maladaptive personal attributes,^19–23 and economic stress¹³ has been linked to maladaptive personal attributes.²⁴ In addition, in the United States, lower socioeconomic status is related to increased rates of cigarette smoking.²⁵

Overall, evidence on the associations of maladaptive personal attributes with lung disease as well as the relation of lung disease to later financial difficulty and maladaptive personal attributes in women is sparse. Therefore, these associations merit further investigation in large-scale studies of women. Indeed, the recent literature suggests that women are particularly susceptible to lung disease.^26,27

Our overall goal was to assess whether maladaptive personal attributes predict the development of lung disease among women. We hypothesized that the linkage between earlier personal attributes and later development of lung disease would be mediated by cigarette smoking. We also predicted that earlier lung disease would be related to both later financial difficulty and maladaptive personal attributes.

METHODS

We derived data from a community-based random sample of families residing in 2 upstate New York counties, Albany and Saratoga. The sampled families were chosen to be representative of families living in these counties with regard to gender, family intactness, family income, and education. There was a close match of the participants’ family income, maternal education, and family structure with data reported in a 1980 survey conducted by the US Census Bureau. A fuller description of the sample appears in Cohen and Cohen.²⁸ Interviews were administered in 1983 (n = 772), 1985–1986 (n = 717), and 1992 (n = 719). The women completed self-administered questionnaires in 2009 (n = 498). Additional information regarding the study methodology is available elsewhere.²⁸

Each of the 498 women who participated in 2009 also participated at least twice between 1983 and 1992. The women’s mean age in 2009 was 65.3 years (SD = 6.2). The percentages of the 498 women who were married, divorced, widowed, and single (i.e., never married) were 66.4%, 15.7%, 17.5%, and 0.4%, respectively. With respect to women’s working status in 2009, 29.3% worked full time, 11.3% worked part time, 42.6% were retired, and 16.8% were classified as “other.” Thirty-nine percent of the participants had completed some college or more. Mean family income in 2009 was $84 842 (SD = $66 049). An exploratory data analysis indicated that there were potential outliers (2.2%) among the participants with extremely high incomes. The percentages of women who smoked were 36.1% in 1983, 33.5% in 1985–1986, 27.4% in 1992, and 14.0% in 2009.

Of the 274 White female participants who took part in the study in 1983 but not in 2009, 104 had died, 27 refused to participate, and 143 were lost to follow-up. After elimination of those who had died, the participation rate in 2009 was 78% of those participating in 1983. Information on cause of death was available for 64 (62%) of the women who died before 2009. The most frequent causes of death were as follows: cancer other than lung cancer (29 participants), heart disease or vascular disease (16 participants), lung cancer (4 participants), and emphysema (3 participants). The 498 women who remained in the study in 2009 had a significantly lower rate of cigarette smoking in 1983 than the rates among the 170 women who were lost to follow-up and the 104 women who had died (36.0%, 42.7%, and 50.5%, respectively; χ²₂ = 8.2, P = .02).

Analyses (t tests) showed that, in 1983, the 498 participating women had significantly higher educational levels than the 170 women who were lost to follow-up (t = 5.97, P < .001) and the 104 women who had died (t = 3.36, P < .01). Also, t tests indicated that in 1983 levels of depression were significantly lower among the participating women than among the women who were lost to follow-up (t = 2.11, P = .04) and the women who had died (t = 2.08, P = .04). There were no significant differences among the participating women, the women lost to follow-up, and the women who had died with respect to anxiety or interpersonal difficulty in 1983 (P > .05).

Measures

Lung disease (1994 to 2009).

Chronic lung disease from 1994 to 2009 was assessed in 2009. Participants reported on the occurrence of COPD and emphysema (or chronic lung disease) in the preceding 15 years; reports were based on physician diagnoses. The lung disease variable was coded as 1 if a participant reported having COPD or emphysema in the preceding 15 years and 0 otherwise. According to Miller et al.,²⁹ individuals can provide reasonably good reports of their morbidity in response to survey questions, and patient self-report questions about disease can be used reliably. Of the 498 participating women, 7.8% were diagnosed with lung disease between 1992 and 2009 (6.7% reported COPD and 5.3% reported emphysema).

Maladaptive personal attributes (1983 and 2009).

Maladaptive personal attributes in 1983, a latent variable, consisted of measures of depression, anxiety, and interpersonal difficulty (C. Zhang, unpublished measure, 2010).^30,31 We also included a latent variable consisting of maladaptive personal attributes in 2009; this variable included measures of depression, anxiety, phobic anxiety, hostility, and externalization. Table 1 presents sample questions for each scale and response ranges for each item. The maladaptive personal attributes variable consisted of 2 types of perceptions: individuals’ perceptions of their own emotional difficulties and of their difficulties in relationships with other people. There is a reciprocal relation between these 2 types of perceptions. Internal distress (e.g., depression and anxiety) may reflect perceptions of difficulty with others. At the same time, interpersonal difficulty may indicate internal distress.

TABLE 1—

Details on Psychosocial Scales Used, Including Sample Items, and Cronbach’s Alpha Values: Albany County and Saratoga County, New York, 1983–2009

Dimension and Scale	No. of Items	Sample Item and Source	Cronbach α
Maladaptive personal attributes: 1983
Depressiona	5	Within the past few years, how much were you bothered by the following: feeling low in energy or slowed down?30	0.80
Anxietya	4	Within the past few years, how much were you bothered by the following: feeling nervous or shaky inside?30	0.74
Interpersonal difficultya	5	How much were you bothered by the following: feeling easily annoyed or irritated?30	0.71
Maladaptive personal attributes: 2009
Depressiona	8	Within the past 5 years, how much were you bothered by feeling hopeless about the future?31	0.90
Anxietya	3	Within the past 5 years, how much were you bothered by feeling anxious?31	0.85
Phobic anxietya	4	Within the past 5 years, how much were you bothered by feeling afraid in open spaces or on the street?31	0.81
Hostilitya	4	Within the past 5 years, how much were you bothered by feeling easily annoyed or irritated?31	0.80
Externalizationa	3	Within the past 5 years, how much were you bothered by feeling others are to blame for most of your troubles?31	0.66
Cigarette smoking: 1983–1992b	1	How many cigarettes do you smoke a day?
Family financial difficulty: 2009
Financial strainc	7	Is it hard to live on your present income?32	0.90
Financial problemsc	14	Because of the current economic conditions, how true is it that you find it difficult to pay for food?33	0.90
Symptoms due to financial worriesc	5	Because of the current economic conditions, how true is it that you sometimes feel anxious? (J. Brook, unpublished measure, 2010)	0.79

^aResponse range: not at all (0), a little (1), somewhat (2), quite a bit (3), extremely (4).

^bResponse range: none (0), less than half a pack a day (1), half a pack to 1 pack a day (2), more than 1 pack a day (3).

^cResponse range: completely untrue (0), mostly untrue (1), somewhat true (2), definitely true (3).

Financial difficulty (2009).

A latent financial difficulty variable included financial strain, problems, and their sequelae in 2009 (Table 1).^32,33

Cigarette smoking (1983 through 1992).

Cigarette smoking from 1983 through 1992 was included as a latent variable. The variable consisted of the participant’s smoking level at each of the 3 measurement points (ratings were made on a scale ranging from none to more than 1 pack per day).

All of these measures have predicted one or more of the following in previous research: depression, anxiety, interpersonal difficulties, phobias, and substance use.^16,34 Moreover, in addition to having predictive validity, these measures were stable over time (Cronbach’s alpha values are presented in Table 1).

Control variables.

Participants’ age and educational level in 1983 and the number of different diseases they were diagnosed with between 1994 and 2009 served as control variables in our analyses. The diseases or symptoms that were controlled included diabetes, hypertension, heart disease or any other vascular problems, heart attack, stroke, and asthma.

Statistical Analysis

We first conducted descriptive analyses with our manifest variables and demographic and control variables. We then used latent variable structural equation modeling³⁵ to examine the empirical validity of the hypothesized pathways. Structural equation modeling is a multivariate statistical method for testing structural models involving constructs that cannot be directly measured. Partial covariance matrices were used as the input matrices, which were created by statistically partialing out the effects of age and educational level in 1983 and the number of diseases between 1994 and 2009 on each of the original manifest variables used. Maximum-likelihood methods (and LISREL 8 software³⁵) were used to estimate the models.

To account for the nonnormal distribution of the model variables, we used the Satorra–Bentler scaled χ² as the test statistic for model evaluation (as recommended by Hu et al.³⁶). We chose 4 fit indices to assess the fit of the models: the LISREL goodness-of-fit index, Bentler’s comparative fit index, the adjusted goodness-of-fit index, and the root mean square error of approximation. Values between 0.9 and 1 on the goodness-of-fit index, comparative fit index, and adjusted goodness-of-fit index indicate that the model provides a good fit to the data.³⁷ Values for the root mean square error of approximation should be below 0.1. The standardized total effects equal the sum of the direct and the indirect effects of each early latent variable (estimated in the analysis) on lung disease and maladaptive personal attributes in 2009, when the participants were in their mid-60s.

We applied the global test and found that there were no significant differences in the structural coefficients in Albany or Saratoga (likelihood ratio test: χ²₆ = 9.55, P = .14). Therefore, we present the analyses for the combined sample.

RESULTS

Table 2 presents the ranges and means for the dependent and independent manifest variables and control variables. As mentioned, 7.8% of the women had lung disease between 1994 and 2009. Paired t-test analyses indicated that there was a significant decrease in smoking from 1983 to 1992 (t = 5.83, P < .001). Seventeen percent of the participants reported at least some symptoms (i.e., the score of the index variable was equal to or greater than 2) on one or more of the 2009 maladaptive personal attribute measures. In addition, 41% reported at least some financial difficulty on one or more of the 2009 financial difficulty measures. These results indicate that a significant number of participants had somewhat severe or severe maladaptive personal attributes or financial difficulties.

TABLE 2—

Sample Descriptive Statistics: Women Residing in Albany County and Saratoga County, New York, 1983–2009 (n = 498)

	Mean (SD)
Dependent and independent variables
Depression: 2009a	0.89 (0.74)
Anxiety: 2009a	0.95 (0.77)
Hostility: 2009a	0.39 (0.52)
Phobic anxiety: 2009a	0.16 (0.39)
Externalization: 2009a	0.23 (0.44)
Financial strain: 2009b	1.77 (0.88)
Financial problems: 2009b	0.82 (0.66)
Symptoms resulting from financial worries: 2009b	0.63 (0.64)
Lung disease: 1994–2009c	0.08 (0.27)
Cigarette smoking: 1992d	0.56 (0.96)
Cigarette smoking: 1985–1986d	0.72 (1.08)
Cigarette smoking: 1983d	0.75 (1.09)
Depression: 1983a	1.04 (0.61)
Anxiety: 1983a	1.12 (0.65)
Interpersonal difficulty: 1983a	0.95 (0.54)
Demographic and control variables
Age, y: 2009	65.32 (2.60)
No. of diseases: 1994–2009	1.03 (1.00)
Educational level, y: 1983	13.03 (2.08)

^aResponse range: not at all (0), a little (1), somewhat (2), quite a bit (3), extremely (4).

^bResponse range: completely untrue (0), mostly untrue (1), somewhat true (2), definitely true (3).

^cResponse range: no (0), yes (1).

^dResponse range: none (0), less than half a pack a day (1), half a pack to 1 pack a day (2), more than 1 pack a day (3).

With regard to the measurement model, all factor loadings were significant (P < .001, 1-tailed test), indicating that the manifest variables were satisfactory measures of the latent constructs. In particular, the fact that all factor loadings were significant for the maladaptive personal attributes latent variable supported our hypothesis that there is a single latent construct (namely, maladaptive personal attributes) underlying the 2 types of perceptions (i.e., those regarding one’s emotional difficulties and those regarding difficulties in relationships with others).

The Satorra–Bentler χ² value was 219.74. The goodness-of-fit index was 0.93, the comparative fit index was 0.97, the adjusted goodness-of-fit index was 0.90, and the root mean square error of approximation was 0.056. These results reflect a satisfactory model fit. The obtained path diagram along with the standardized regression coefficients are depicted in Figure 1.

FIGURE 1—

Path diagram depicting standardized pathways to women’s (n = 498) maladaptive personal attributes: Albany county and Saratoga county, New York, 1983–2009.

Note. Values in parentheses are t statistics. Age and educational level in 1983 and number of diseases between 1994 and 2009 were statistically controlled. Goodness-of-fit index = 0.93; comparative fit index = 0.97; adjusted goodness-of-fit index = 0.90; root mean square error of approximation = 0.056. The sample size was n = 498.

*P < .05; **P < .01; ***P < .001 (1-tailed test).

All standardized pathways depicted in Figure 1 were statistically significant (P < .05; 1-tailed test). First, the association between maladaptive personal attributes in 1983 and lung disease between 1994 and 2009 was mediated by cigarette smoking from 1983 to 1992 (b = 0.17; t = 3.28, P < .001). Smoking was associated with lung disease (b = 0.33; t = 5.08, P < .001). Second, lung disease was associated with family financial difficulty in 2009 (b = 0.09; t = 2.13, P < .05), which in turn was associated with maladaptive personal attributes in 2009 (b = 0.35; t = 6.30, P < .001). Third, earlier maladaptive personal attributes were associated with later maladaptive personal attributes (b = 0.43; t = 7.46, P < .001) and family financial difficulty (b = 0.29; t = 5.77, P < .001).

Table 3 presents the standardized total effects (sum of direct effects and indirect effects) of each of the latent or manifest constructs on participants’ maladaptive personal attributes in their mid-60s. The total effects of maladaptive personal attributes and cigarette smoking on lung disease are also shown. The results indicate that all of the total effects presented were significant (P < .05, 1-tailed test).

TABLE 3—

Standardized Total Effects of Predictors of Lung Disease and Later Maladaptive Personal Attributes and Family Financial Difficulties: Women Residing in Albany County and Saratoga County, New York, 1983–2009

Latent Variable (Predictor)	Maladaptive Personal Attributes: 2009, b (t)	Chronic Lung Disease: 1994–2009, b (t)
Family financial difficulty: 2009	0.35 (6.30)***	…
Chronic lung disease: 1994–2009	0.03 (2.03)*	…
Cigarette smoking: 1983–1992	0.01 (1.81)*	0.33 (5.08)***
Maladaptive personal attributes: 1983	0.53 (9.05)***	0.06 (2.64)**

Note. Age and educational level in 1983 and number of diseases between 1994 and 2009 were statistically controlled. The sample size was n = 498.

*P < .05; **P < .01; ***P < .001 (1-tailed).

DISCUSSION

This study highlights the importance of lung disease as an intervening factor between women’s predisposing maladaptive personal attributes and later maladaptive personal attributes. It is important to assess this relationship given that, as noted earlier, women are particularly susceptible to lung disease. Our analysis supports a model in which maladaptive personal attributes predict cigarette smoking, cigarette smoking is associated with lung disease, lung disease predicts financial stress, and financial stress is related to later maladaptive personal attributes (Figure 1).

Our study is unique in several ways. First, previous investigators have examined the separate associations between lung disease and emotional difficulty or financial difficulty. Departing from previous research, we examined all of these dimensions in a single multidimensional model. Second, our findings confirm a number of plausible pathways in a longitudinal setting. Our longitudinal design allowed us to investigate the earlier predictors as well as possible consequences of lung disease. Third, this is the first longitudinal study covering more than 2 decades to examine the maladaptive personal attributes related to lung disease in a community sample of women. Fourth, we focused on earlier maladaptive personal attributes, cigarette smoking, and later lung disease. Finally, we examined the association between earlier lung disease and later financial difficulties and maladaptive personal attributes.

Not surprisingly, our findings confirmed the direct linkage from earlier cigarette smoking to later lung disease (Figure 1). The role of cigarette smoking in causing lung disease is, of course, well known.⁴

In contrast to the multitude of studies on the relationship of smoking to lung disease, there is scant literature on the psychological factors that may be related to lung disease.^9,12 Our findings indicate that psychological maladjustment (e.g., depression, anxiety) is related to smoking,^13,14 which in turn is related to later lung disease. Therefore, as can be seen in Figure 1, it is likely that psychological maladjustment is related to lung disease through the mediating role of smoking. Indeed, our total effects analysis of psychological maladjustment and lung disease supports this interpretation (Table 2).

Furthermore, the relationship between maladaptive personal attributes and lung disease appears to be reciprocal. Not only do earlier maladaptive personal attributes predict later lung disease, but lung disease is associated with later maladaptive personal attributes. In a related vein, several investigators^8,38 have reported that depressive symptoms are prevalent in patients with severe COPD.

There is relatively little research on the effects of lung disease on family financial difficulty.^17,39 One possible explanation for the relationship between earlier lung disease and later family financial difficulty has to do with the fact that individuals with lung disease have difficulty obtaining or maintaining employment.¹⁸ In addition, patients with lung disease have high medical bills.

Our results suggest that family financial difficulty, even if not great, is associated with psychological maladjustment, as indicated by depression, anxiety, phobic anxiety, hostility, and externalization.^40,41 These results are consistent with earlier studies linking financial difficulty with depression²⁴ and hostility. Financial difficulty may interfere with an individual’s ability to cope with physical as well as emotional issues. This may lead to the individual experiencing stress manifested in lower self-esteem, anxiety about the future, and depression about his or her current situation. As mentioned, our model suggests that lung disease predicts financial stress and that financial stress predicts maladaptive personal attributes.

Limitations and Strengths

Our study involved several potential limitations. First, it was limited to self-reporting of cigarette smoking and depression, and the participants’ reports of lung disease obtained from their physicians. However, self-reporting of cigarette smoking and lung disease in the United States has been found to be reasonably accurate.^29,42 Nevertheless, the bias resulting from the omission of depressed women with higher smoking rates may be important. Second, our study was restricted to White women in late midlife. Generalizing from this sample must be done with caution. Replication of the findings is needed to address this issue in ethnically diverse groups of men and women. As noted earlier, women may be particularly susceptible to lung disease.^26,27 Because women report greater depression and anxiety than men,⁴³ our findings highlight the significance of maladaptive personal attributes in lung disease.

Third, levels of depression and smoking were lower among participants who were included in the study than among those who were not included because they had died or were lost to follow-up. This is a relatively common finding in longitudinal studies.⁴⁴ Fourth, our study design precluded an analysis of secular changes in smoking. Future research should be designed to incorporate examinations of secular changes in smoking among both men and women.

With respect to the strengths of the study, there are few longitudinal data sets spanning more than 25 years available on the association of earlier maladaptive personal attributes with lung disease, later financial strain, and ultimately later maladaptive personal attributes. Consequently, this study helps to move the field forward by providing evidence of some of the potential psychosocial determinants and consequences of lung disease covering a period of more than 2 decades.

It would be helpful for physicians and other health care providers treating female patients with lung disease to consider psychological issues as well as physical issues. A brief inventory of psychological symptoms and smoking could be sufficient to initiate referral to health care providers for further evaluation. Our findings also raise the possibility that helping individuals to stop smoking (e.g., in smoking cessation programs) may improve health behaviors and reduce the probability of lung disease. A reduction in lung disease may result in less financial stress and ultimately greater psychological adjustment.

Conclusions

Our results suggest that there is a cycle whereby earlier maladaptive personal traits predict smoking, smoking predicts lung disease, lung disease is associated with financial stress, and financial stress is correlated with later maladaptive personal traits. Health care providers treating patients with lung disease should initiate actions to break this self-amplifying cycle. By aggressively addressing both maladaptive personal attributes and smoking, health care providers may be able to contribute to the prevention of lung disease before it begins and arrest the progression of disease once it has started.