Mental and Physical Distress and High Risk.8

7/23/2019 Mental and Physical Distress and High Risk.8

1/7

Mental and Physical Distress and High-RiskBehaviors Among Reproductive-Age Women

Indu B. Ahluwalia, MPH , PhD , Karin A. Mack, PhD , and Ali Mokdad, PhD

OBJECTIVE: To examine the prevalence of mental and phys-ical distress indicators among women of reproductive ageand the association of these indicators with cigarette smok-ing and alcohol use, by pregnancy status.METHODS:TheBehavioral RiskFactor SurveillanceSystemdata for several years were aggregated across states and weighted for this analysis. Seven measures of self-reportedmental and physical distress and general health were ex-amined along with demographic variables.RESULTS: Overall, 6.7% (95% condence interval CI 6.56.9) of women reported frequent physical distress, 12.3%(95% CI 12.012.6) reported frequent mental distress, 9.9%(95% CI 9.410.4) reported frequent depression, 18.4%(95% CI 17.819.1) reported feeling anxious, and 34.3%(95% CI 33.535.1) reported that they frequently didnot get enough rest. At the time of the survey 4.6% of the women were pregnant. Pregnant women were less likely thannonpregnant women to report frequent mental distress.Although there was attenuation of cigarette smoking andalcohol use during pregnancy, those with mental and phys-ical distress were more likely to consume cigarettes and

alcohol than were those without such experiences.CONCLUSION:Highproportions of reproductive-age womenreport frequent mental and physical distress. Women ex-periencing mentalandphysicaldistress were more likely toreport consuming cigarettes and alcohol than women with-out such experiences. (Obstet Gynecol 2004;104:47783. 2004 by The American College of Obstetricians andGynecologists.)LEVEL OF EVIDENCE: III

Research shows that 20% to 25% of women will experi-ence depression during their life and that depression is

common among women of child bearing age.16

Depres-sion is one of the most common reasons for a nonobstet-ric hospital stay among women 18 to 44 years old.7Gender differences in rates of depression are generallynot observed until after puberty and appear to decrease

after menopause; hormones, along with stress and otherpredisposing biologic, social, and psychosocial factors,may play a role in experiences with depression.1,2,58

Women experience higher prevalence of both mentaldistress (eg, depression, mood disorders) and physicaldistress (eg, activity limitation) than men, and the prev-alence of these is even higher for women of reproductiveage.813

Socioeconomic factors such as marital status, educa-tion, and family history of mood disorders are linkedwith health-related behaviors and health outcomes.14,15Studies have shown that poor mentalandphysical healthis related to participation in high-risk behaviors of ciga-rette smoking and alcohol and illicit drug use and thatthese factors in turn are associated with increased mor-tality and morbidity.3,4,1623 Furthermore, mental andphysical health problems during pregnancy are linked topoor attendance at antenatal clinics, continuation of high-risk behaviors (eg, cigarette smoking), poor socialfunctioning, preeclampsia, low birth weight, preterm

births, and problems with social and emotional develop-mentamongchildren.2427 Two recently published stud-ies focused on the high prevalence of depression among pregnant women and the lack of attention to systematicscreenings and counseling of women during this criticalperiod.28,29 In fact, some researchers and practitionershave suggested integrating behavioral healthcare withroutine practice of obstetrics and gynecology, becausesuch practitioners are often the primary care providersfor reproductive-age women.30 The purpose of thisstudy was to examine the distribution of mental andphysical health distress measured by the Health RelatedQuality of Life indicators and the association betweenthese indicators and cigarette and alcohol consumptionamong reproductive-age women. We selected women of reproductive age for several reasons, including higherrates of mental and physical distress, life-stage, and pre-vention opportunities available to them at this time. Westratied our analysis by pregnancy status because manywomen change their own behaviors while others areadvised to avoid high-risk behaviors.

From the Division of Adult and Community Health, National Center for Chronic Disease Prevention and Health Promotion, and Division of Unintentional Injury,National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia.

VOL. 104, NO. 3, SEPTEMBER 2004477 2004 by The American College of Obstetricians and Gynecologists. 0029-7844/04/$30.00

Published by Lippincott Williams & Wilkins. doi:10.1097/01.AOG.0000137920.58741.26


2/7

MATERIALS AND METHODS

We analyzed data from the Behavioral Risk Factor Sur-veillance System (BRFSS) for 1998, 2000, and 2001.Behavioral Risk Factor Surveillance System data from1999 were not included because the Health RelatedQuality of Life module was not part of the 1999 Behav-

ioral Risk Factor Surveillance System survey. The Be-havioral Risk Factor Surveillance System is an ongoing,state-based, random-digit-dialed telephone survey of thenoninstitutionalized US population 18 years of age orolder. It is used to monitor health-related behaviors andcharacteristics in all 50 states, the District of Columbia,and the 3 US territories of Puerto Rico, US VirginIslands, and Guam. The Behavioral Risk Factor Surveil-lance System survey included a core set of 4 HealthRelated Quality of Life measures, collected by all states,and an optional rotating module, selected by certainstates, with additional Health Related Quality of Lifequestions that were administered by 13 states in 1998,23states in 2000, and 13 states in 2001. Response ratesvaried by state, the median response rates were 59.1%for 1998; 48.9% for 2000; and 51.1% for 2001. Of the156,428 female Behavioral Risk Factor Surveillance Sys-tem participants of reproductive age, 147,532 (94%) hadinformation on pregnancy status available. The percent-age excluded for missing data ranged from less than0.2% for womens age to 11% for income. BehavioralRisk Factor Surveillance System data quality is optimalwhen compared with other national surveys, data are

shown to be reliable and valid, and additional informa-tion is available online at http://www.cdc.gov/BehavioralRisk Factor Surveillance System.31 This study was ap-proved by the Institutional Review Board of the Centersfor Disease Control and Prevention.

We used both core and module Health Related Qual-ity of Life indicators to assess the nature and extent of self-reported physical andmental distress among womenof reproductive age (Box). We used generalself-reportedhealth status (n 147,373), recent physical health (n146,272), recent mental health (n 145,838), and recentactivity limitation due to poor physical or mental health(n 88,101). Health Related Quality of Life indicatorsfor recent depression (n 40,638), stress and anxiety(n 40,502), and lack of rest (n 40,725) were assessedfrom the optional modules. These Health Related Qual-ity of Life measures have been validated among severalpopulations in the United States and other countries.32

Measures in this study were dichotomized by using 14 ormore days as the cutoffvalue for determining the chronicpresence of mental and physical distress.913

Questions Used to Assess the Health RelatedQuality of Life Measures, Behavioral Risk FactorSurveillance System

Health Related Quality of Life Questions From the Core Module

General Health Status: In general, would yousay your health is excellent, very good, good,fair, or poor?

Physical Health: Thinking about your physicalhealth, which includes physical illness and injury,for how many days during the past 30 days wasyour physical health not good?

Mental Health: Thinking about your mentalhealth, which includes stress, depression, andproblems with emotions, for how many daysduring the past 30 days was your mental healthnot good?

Activity Limitation: During the past 30 days, forabout how many days did poor physical or men-tal health keep you from doing usual activities,such as self care, work, or recreation?

Health Related Quality of Life Questions From the Optional Module *

Depression: During the past 30 days, for abouthow many days have you felt sad, blue, or de-pressed?

Stress and Anxiety: During the past 30 days, forabout how many days have you felt worried,tense, or anxious?

Lack of Rest: During the past 30 days, for abouthow many days you felt that you did not getenough rest or sleep?

*A selected set of states used the optional modulewith these questions.

We considered a number of demographic variables inthe analysis including womens age, race, education,marital status, whether they had any children, income,and health insurance coverage. The 2 health-risk behav-iors examined were cigarette smoking and alcohol use. These behaviors were examined because pregnantwomen are advised to refrain from smoking and using any alcohol and because these have been linked tomental distress and adverse pregnancy outcomes.

478 Ahluwalia et al Mental and Physical Distress Among Women OBSTETRICS & GYNECOLOGY


3/7

Women were considered to have a history of cigarettesmoking if they reported smoking at least 100 cigarettesin their lifetime and to be current smokers if they re-ported smoking every day or some days. Alcoholuse was dened as having had at least one drink of analcoholic beverage during the past month. Binge drink-ing was dened as having consumed 5 or more drinks onone occasion in the previous month. We used softwarefor survey data analysis (SUDAAN, Research TriangleInstitute, Research Triangle Park, NC) to account for thecomplex sample design and to generate prevalence esti-mates and standard errors and to perform multivariateanalyses.

RESULTS

The overall demographic characteristics of the popula-tion indicate that more than 50% of the women were between 30 to 44 years of age; 67.3% of the populationstudied was white, 11.4% black, 15.8% Hispanic, and

5.5% were categorized as other. The majority were mar-ried, had children, had incomes of $25,000 or above, andreported having health insurance coverage (Table 1).Overall, 4.6% (6,208) of the women were pregnant at thetime of the interview. The demographic prole of preg-nant women was quite similar to that of nonpregnantwomen on race, education level, and income. However, ahigher proportion of pregnant women were younger, mar-ried, and reported having health insurance (Table 1).

The majority of women reported that their generalhealth was excellent (25.8%; 95% condence intervalCI 24.426.2) or very good (36.4%; 95% CI 36.0

36.8); more than a quarter reported that their health wasgood (28.2%; 95% CI 27.628.4), and 9.3% (95% CI9.09.6) reported that their health was fair or poor(Table 2). Overall, 6.7% (95% CI 6.56.9) reportedfrequent physical distress, 12.3% (95% CI 12.012.6)reported frequent mental distress, and 7.1% (95% CI6.77.4) reported frequent activity limitation due to poor

Table 1. Demographic Characteristics of Reproductive-Age Women by Pregnancy Status, Behavioral Risk Factor Surveil-lance System

Demographic characteristics Overall (N 147,532) Pregnant (n 6,208) Not pregnant (n 141,324)

Age in years1824 24.3 (23.924.7) 32.5 (30.534.6) (23.424.3)2529 17.4 (17.117.7) 27.9 (26.229.7) 16.9 (16.517.2)3034 19.0 (18.619.3) 25.3 (23.626.9) 18.7 (18.318.9)3539 20.4 (20.120.7) 11.7 (10.412.9) 20.8 (20.521.2)4044 19.0 (18.719.3) 2.6 (1.93.2) 19.8 (19.520.2)

Race or ethnicityBlack 11.4 (11.111.7) 10.8 (9.512.0) 11.4 (11.111.7)Hispanic 15.8 (15.316.3) 17.3 (15.619.1) 15.7 (15.216.2)Other 5.5 (5.25.7) 6.2 (4.97.5) 5.5 (5.25.6)White 67.3 (66.767.8) 65.7 (36.667.8) 67.4 (66.967.9)

EducationHigh school 10.3 (9.910.6) 12.9 (11.414.4) 10.2 (9.810.5)

High school 29.7 (29.330.1) 29.3 (27.331.2) 29.7 (29.330.1)Some college 30.9 (30.531.3) 27.6 (25.829.4) 31.1 (30.731.5)College 29.1 (28.729.5) 30.2 (28.531.9) 29.0 (28.629.4)

Marital statusSingle 27.8 (27.428.2) 17.1 (15.418.7) 28.3 (27.928.7)Divorced or separated or widowed 12.2 (11.912.5) 5.4 (4.26.6) 12.6 (12.312.8)Couple 4.8 (4.65.0) 6.7 (5.57.8) 4.7 (4.44.9)Married 55.2 (54.855.6) 70.9 (68.972.9) 54.5 (54.054.9)

Have childrenYes (65.666.4) 66.7 (64.868.6) 65.9 (65.666.4)No 34.0 (33.634.4) 33.3 (31.435.2) 34.1 (33.634.4)

Income level in dollars15,000 12.0 (11.612.4) 10.9 (9.512.3) 12.1 (11.712.4)

15,00024,9999 18.9 (18.519.3) 20.9 (19.122.7) 18.9 (18.519.2)25,00049,999 35.4 (34.935.9) 35.0 (32.937.1) 35.4 (34.935.9)50,00074,999 17.4 (17.117.7) 16.3 (14.817.8) 17.4 (17.017.8)

75,000 16.2 (15.916.6) 16.9 (15.318.4) 16.3 (15.916.6)Health Insurance coverage

Yes 82.0 (81.682.4) 88.3 (86.989.7) 81.7 (81.382.1)No 18.0 (17.618.4) 11.7 (10.313.1) 18.3 (17.918.7)

Values are percentage and (95% condence interval). Percentages may not add to 100 due to rounding.

479VOL. 104, NO. 3, SEPTEMBER 2004 Ahluwalia et al Mental and Physical Distress Among Women


4/7

mentalor physical health(Table 2). Approximately 9.9%(95% CI 9.410.4) reported that they frequently felt sad, blue, or depressed; 18.4% (95% CI 17.819.1) reportedfeeling frequently worried, tense, or anxious; and 34.3%(95%CI 33.535.1) reported that they frequently didnotget enough rest or sleep. Nonpregnant women had ahigher prevalence of cigarette smoking (25.1%; 95% CI24.725.5) than pregnant women (12.3%; 95% CI 11.013.6), as well as higher rates of alcohol use in the pastmonth (54.7% compared with 11.6%) and binge drink-ing (19.8% compared with 3.8%).

Among nonpregnant women, those who reported fairor poor health were more likely (odds ratio OR 1.6;95% CI 1.41.7) to report smoking cigarettes than thosewho assessedtheir general health status to be excellent orgood after adjusting for several demographic character-istics (Table 3). Women with frequent physical distresswere more likely (OR 1.5; 95% CI 1.41.7) to smokecigarettes than those who did not report such distress.

Those with frequent mental distress (OR 2.0; 95% CI1.92.1), frequent activity limitation (OR 1.6; 95% CI1.41.8), depression (OR 2.2; 95%CI 1.92.5), frequentexperiences of stress and anxiety (OR 1.9%; 95% CI1.72.1), or frequent lack of rest (OR 1.5; 95%CI 1.41.7) were more likely to smoke cigarettes than those whodid not report having such problems. The magnitude of the association was strongest for those who reportedfrequent mental distress or depression.

Similarly, among pregnant women, those who re-ported their general health to be fair or poor were morelikely to report smoking cigarettes (OR 2.4; 95% CI1.53.8). Pregnant women who reported frequent phys-ical distress (OR 1.7; 95% CI 1.12.6) or mental healthdistress (OR 2.5; 95% CI 1.73.7) were more likely toreport smoking cigarettes than pregnant women whodidnot report these. It is interesting to note that the magni-tude of the association between 3 of the Health RelatedQuality of Life indicators (ie, fair or poor health, fre-

Table 2. Health-Related Quality-of-Life and Selected Behavioral Indicators by Pregnancy Status, Behavioral Risk FactorSurveillance System

Health-related quality-of-lifemeasures Overall (N 147,532) Pregnant (n 6,208) Not pregnant (n 141,324)

General health: fair or poor ( 14 days) 9.3 (9.09.6) 6.4 (5.47.4) 9.5 (9.29.8)Frequent physical distress ( 14 days) 6.7 (6.56.9) 7.1 (6.28.1) 6.7 (6.56.9)Frequent mental distress ( 14 days) 12.3 (12.012.6) 7.7 (6.78.7) 12.5 (12.312.8)Frequent activity limitation ( 14 days) 7.1 (6.77.4) 8.0 (6.69.5) 7.0 (6.77.3)Frequent depression ( 14 days)* 9.9 (9.410.4) 8.1 (6.010.2) 10.0 (9.410.5)Frequent stress or anxiety ( 14 days)* 18.4 (17.819.1) 16.2 (13.718.7) 18.5 (17.819.2)Frequent lack of rest ( 14 days)* 34.3 (33.535.1) 38.3 (34.841.8) 34.1 (33.334.9)Behaviors

Current cigarette smoker 24.5 (24.124.9) 12.3 (11.013.6) 25.1 (24.725.5)Drank alcohol in past month 52.8 (52.153.5) 11.6 (9.813.4) 54.7 (54.055.4)Binge drank in past month 19.4 (18.820.0) 3.8 (2.45.2) 19.8 (19.220.4)

Values are percentage and (95% condence interval). Percentages may not add to 100 due to rounding.* Data on these indicators were collected with an optional module, and only a selected set of states used the module.

Table 3. Association Between Health-Related Quality-of-Life Indicators and Cigarette Smoking Among Pregnant andNonpregnant Women, Behavioral Risk Factor Surveillance System

Health-related quality-of-life indicators

Cigarette smokingPregnant Not pregnant

Crude OR(95% CI)

Adjusted OR(95% CI) *

Crude OR(95% CI)

Adjusted OR(95% CI) *

General health (fair or poor) 2.2 (1.53.2) 2.4 (1.53.8) 1.7 (1.61.9) 1.6 (1.41.7)Frequent physical distress ( 14 days) 1.7 (1.22.5) 1.7 (1.12.6) 1.8 (1.72.0) 1.5 (1.41.7)Frequent mental distress ( 14 days) 3.2 (2.34.4) 2.5 (1.73.7) 2.5 (2.32.7) 2.0 (1.92.1)Frequent activity limitation ( 14 days) 1.8 (1.02.8) 1.5 (0.92.6) 2.0 (1.82.1) 1.6 (1.41.8)Frequent depression ( 14 days) 1.8 (1.03.2) 1.3 (0.62.7) 2.6 (2.32.9) 2.2 (1.92.5)Frequent experience of stress or anxiety (14 days) 2.1 (1.33.3) 1.3 (0.72.5) 2.3 (2.12.5) 1.9 (1.72.1)Frequent lack of rest ( 14 days) 1.8 (1.22.8) 2.0 (1.23.3) 1.6 (1.51.7) 1.5 (1.41.7)OR, odds ratio; CI, condence interval.

* Adjusted for age, race, education, marital status, income, and whether women had children and health insurance. Data on these indicators were collected with an optional module, and only a selected set of states used the module.



5/7

quent mental distress, and frequent lack of rest) andsmoking was stronger among pregnant than nonpreg-nant women.

Rates of alcohol use and binge drinking were loweramong pregnant than among nonpregnant women. Be-cause of the small numbers of women in the pregnant binge drinking category, we could not assess the associ-ation between Health Related Quality of Life indicatorsand binge drinking. As shown in Table 4, among non-pregnant women those with frequent mental distress(OR 1.2; 95% CI 1.11.3), frequent depression (OR 1.3;95% CI 1.11.5), or frequent stress and anxiety (OR 1.3,95% CI 1.11.5) were more likely to report drinking anyalcohol in the previous month. Most Health RelatedQuality of Life measures were not found to be signi-cantly associated with alcohol use among pregnantwomen.

DISCUSSION

Our ndings show that women of reproductive ageexperience substantial amounts of physical and mentaldistress, depression, and stress and anxiety, and a highproportion do not get enough rest or sleep. Moreover,pregnant women were less likely than nonpregnantwomen to report fair or poor health and frequent mentaldistress but were more likely to report frequent physical

distress and activity limitation. It is possible that somedifferences can be explained by biologic, physical, orpsychological changes related to pregnancy and men-strual cycles.1,2

Our ndings are consistent with those from studies inwhich women with physical or mental distress weremore likely to engage in high-risk behaviors of cigarettesmoking and substance misuse.3,4,1623 Although fewerpregnant women reported smoking cigarettes, those whowere experiencing poor overall health, frequent mental

distress, or frequent lack of rest were signicantly morelikely to report smoking than those without such experi-ences. In general, the emotional health of reproductive-age women may be associated with engaging in high-risk behaviors such as substance misuse, which may havelong-term consequences for them and their families.1627,31 Available encounters between women and providersshould be used to educate women and to focus onprevention, given that many women in the reproductive-age group could be at risk for having unintended preg-nancies and may be experiencing mental or physicaldistress and engaging in high-risk behaviors.

Our ndings are subject to several limitations. First,the cross-sectional nature of the data did not allow us toestablish a causal relationship. Second, because the Be-havioral Risk Factor Surveillance System is based ondata from a telephone surveys, the results may not begeneralizable to women who do not have telephones oruse only wireless phones. Finally, we were unable todetermine the stage of pregnancy from Behavioral RiskFactor Surveillance System data. However, we have alarge representative sample of US reproductive-agewomen, which enabled us to examine a number of Health Related Quality of Life indicators and their asso-ciation with high-risk behaviors.

Our ndings highlight the importance of examining

the association between mental and physical distressmeasured by Health Related Quality of Life indicatorsand high-risk behaviors. Providers should assess themental health status of pregnant women during prenatalcare visits and that of nonpregnant women during visitsfor routine checkups, family planning visits, and well-child visits for those with children. These visits provideopportunities to counsel andsupport to women engaging in high-risk behaviors or having difculty coping withhealth conditions or social stressors. Public health agen-

Table 4. Association Between Health-Related Quality-of-Life Indicators and Alcohol Use Among Pregnant and NonpregnantWomen, Behavioral Risk Factor Surveillance System

Health-related quality-of-life indicators

Alcohol UsePregnant Not Pregnant

Crude OR(95% CI)

*Adjusted OR(95%)

Crude OR(95% CI)

*Adjusted OR(95% CI)

General health (fair or poor) 1.2 (0.62.2) 1.5 (0.73.1) 0.5 (0.40.5) 0.7 (0.60.7)Frequent physical distress ( 14 days) 0.8 (0.41.7) 0.9 (0.42.0) 0.6 (0.50.7) 0.7 (0.60.8)Frequent mental distress ( 14 days) 1.0 (0.51.8) 1.3 (0.72.5) 1.1 (1.01.2) 1.2 (1.11.3)Frequent activity limitation ( 14 days) 1.4 (0.53.6) 1.4 (0.63.5) 0.5 (0.40.6) 0.6 (0.50.7)Frequent depression ( 14 days) 1.4 (0.53.6) 2.1 (0.76.6) 1.1 (0.91.2) 1.3 (1.11.5)Frequent experience of stress or anxiety (14 days) 1.1 (0.52.5) 1.0 (0.42.4) 1.2 (1.11.4) 1.3 (1.11.5)Frequent lack of rest ( 14 days) 0.6 (0.31.0) 0.4 (0.20.8) 1.0 (0.91.1) 1.0 (0.91.1)OR, odds ratio; CI, condence interval.

* Adjusted for age, race, education, marital status, income, and whether women had children and health insurance. Data on these indicators were collected with an optional module, and only a selected set of states used the module.



6/7

cies, organizations, and primary health care providersneed to develop, implement, and promote integratedprograms for women that take into account mental andphysical health. Interventions that integrate social and behavioral health along with physical health would beuseful for long-term behavior change that would benetnot only women but also their families.

REFERENCES

1. National Institute of Mental Health. Fact sheet: womenhold up half the sky. DHHS Pub. No. 014607. Bethesda(MD): Published Jan 1, 2001. Available at: http://www.nimh.nih.gov/publicat/womensoms.cfm. Retrieved June25, 2004.

2. Mazure C, Keita GP, Blehar MC. Summit on Women andDepression: proceedings and recommendations. Washing-ton (DC): American Psychological Association; 2002. Avail-able at: http://www.apa.org/pi/wpo/women&depression.pdf.Retrieved June 25, 2004.

3. Regier DA, Narrow WE, Rae DS, Manderscheid RW,Locke BZ, Goodwin FK. The de facto mental and addic-tive disorders service system: Epidemiologic Catchment Area prospective rates of disorders and services. Arch GenPsychiatr 1993;50:8594.

4. Kessler RC, McGonagle KA, Zhao S, Nelson CB, HughesM, Eshleman S, et al. Lifetime and 12 month prevalence of DSM-III-R psychiatric disorders in the United States:results from the National Comorbidity Survey. Arch GenPsychiatr 1994;51:819.

5. Yonkers KA, Chantilis SJ. Recognition of depression inobstetric/gynecology practices. Am J Obstet Gynecol1995;173:6326.

6. Bebbington PE, Dunn G, Jenkins R, Lewis G, Brugha T,Farrell M, et al. The inuence of age and sex on theprevalence of depressive conditions: report from theNational Survey of Psychiatric Morbidity. Psychol Med1998;28:919.

7. Jiang HJ, Elixhauser A, Nicholas J, Steiner C, Reyes, Bier-man AS.Careofwomenin U.S. Hospitals,2000.HCUPFactBook No. 3; AHRQ Publication No. 020044. Rockville(MD): Agency for Healthcare Research and Quality; 2002.

8. Sherrill JT, Anderson B, Frank E, Reynolds CF 3rd, TuXM, Patterson D, et al. Is life stress more likely to provokedepressive episodes in women than in men? Depress Anx-iety 1997;6:95105.

9. Ahluwalia IB, Holtzman D, Mack K, Mokdad A. Health-related quality of life among women of reproductive age:Behavioral Risk Factor Surveillance System (BRFSS),19982001. J Womens Health (Larchmt) 2003;12:59.

10. Centers for Disease Control and Prevention. Measuring healthy days. Atlanta (GA): Centers for Disease Controland Prevention; 2000.

11. Health-related quality of life andactivity limitation in eightstates, 1995. MMWR Morb Mortal Wkly Rep 1998;47:13440.

12. Self-reported frequent mental distress among adults in theUnited States, 19931996. MMWR Morb Mortal WklyRep 1998;47:32531.

13. Health-related quality-of-life measuresUnited States,1993. MMWR Morb MortalWkly Rep1995;44:195200.

14. Kawachi I, Kennedy BP, Gupta V, Prothrow-Stith D.Womens status and the health of women and men: a viewfrom the states. Soc Sci Med 1999;48:2132.

15. Khan R, Wise P, Kennedy B, Kawachi I. State incomeinequality, household income, and maternal mental andphysicalhealth: cross sectionalnational survey. BMJ 2000;321:13115.

16. Ford E, Moriarty DG, Zack MM, Mokdad AH, ChapmanD. Self-reported body mass index and health-related qual-ity of life: ndings from the Behavioral Risk Factor Sur-veillance System. Obes Res 2001;9:2131.

17. Hoffman S, Hatch M. Depressive symptomatology during pregnancy: evidence for an association with decreasedfetal growth in pregnancies of lower social class women.Health Psychol 2000;19:53543.

18. Hathaway JE, Mucci LA, Silverman JG, Brooks DR,Mathews R, Pavlos LA. Health status and health care useof Massachusetts women reporting partner abuse. Am JPrev Med 2000;19:3027.

19. Harwell TS,Spence MR.Population surveillance forphys-ical violence among adult men and women, Montana1998. Am J Prev Med 2000;19:3214.

20. Unger J. Sedentarylifestyleas a risk factorforself-reportedpoor physical and mental health. Am J Health Promot

1995;10:157.21. Regier DA, Farmer ME, Rae DS, Locke BZ, Keith SJ, JuddLL, et al. Comorbidity of mental disorders with alcoholand other drug abuse: results from the EpidemiologicalCatchment Area (ECA) Study. JAMA 1990;264:251118.

22. Roeloffs CA, Wells KB, Ziedonis D, Tang L, Unutzer J.Problem substance use among depressed patients in man-aged primary care. Psychosomatics 2002;43:40512.

23. Kessler RC, Berglund P, Demler O, Jin R, Koretz D,Merikangas KR, et al. The epidemiology of major depres-sive disorder: results from the National Comorbidity Sur-vey Replication (NCS-R). JAMA 2003;289:3095105.

24. Kurki T, Hilesmaa V, Raitasalo R, Mattila H, YlikorkalaO. Depression and anxiety in early pregnancy and risk forpreeclampsia. Obstet Gynecol 2000;95:48790.

25. Hedegaard M, Henrisksen TB, Sabroe S, Secher NJ. Psy-chological distress in pregnancy and preterm delivery.BMJ 1993;307:23439.

26. Pagel MD, Smilstein G, Regen H, Montano D. Psycholog-ical inuences on new-born outcomes: a controlled pro-spective study. Soc Sci Med 1990;30:597604.

27. Zhu SH, Valbo A. Depression and smoking during preg-nancy. Addict Behav 2002;27:64958.



7/7

\28. Evans J, Heron J, Francomb H, Oke H,Golding J. Cohortstudy of depressed mood during pregnancy and afterchildbirth. BMJ 2001;323:25760.

29. Marcus SM, Flynn HA, Blow FC, Barry KL. Depressivesymptoms among pregnant women screened in obstetricsettings. J Womens Health 2003;12:37380.

30. Cassidy JM, Boyle VA, Lawrence HC. Behavioral healthcare integration in obstetrics and gynecology. Med-GenMed 2003;5:19. Available at: http://www.medscape.com/viewarticle/453592. Retrieved June 28, 2004.

31. Centers for Disease Control and Prevention. PublicHealth surveillance for behavioral risk factors in a chang-ing environment. MMWR Morb Mortal Wkly Rep 2003;52(RR-9).

32. Moriarty DG, Zack MM, Kobau R. The Centers forDisease Control and Preventions healthy daysmeasurespopulation tracking of perceived physical and mentalhealth over time. Health Qual Life Outcomes 2003;1:37. Available at: http://www.hqlo.com/content/1/1/37.Retrieved June 25, 2004.

Address reprint requests to: Indu Ahluwalia, MPH, PhD,Division of Adult andCommunity Health, Centers forDiseaseControl andPrevention, 4770BufordHighway, NE,Mail-stopK-66, Atlanta, GA 303413724; e-mail: [email protected].

Received April 12, 2004. Received in revised form June 10, 2004. Accepted June 17, 2004.


Documents

Mental and Physical Distress and High Risk.8