Public Health Briiefs

officers in New Jersey, the findings areconsistent with criticisms of the Environ-mental Protection Agency (EPA) for notinvolving local people in the site remedi-ation process and the call for two-waycommunication between agencies andstakeholders.4-7

I offer two recommendations to pro-mote interaction. First, the EPA, theAgency for Toxic Substances and DiseaseRegistiy, and state agencies should re-quire their site managers to formally meetwith local health officers to obtain infor-mation about environmental, health, andquality-of-life conditions and land usegoals that might affect remediation; avail-ability and quality of local data; and likelylocal reaction to various health and envi-ronmental surveys and remediation op-tions. These meetings should occurwhen-ever the agency is brainstorming or hasreached tentative conclusions.

Second, local health officerswho feelthat their access to the decision-makingprocess is being denied should use their

state organization to arrange meetingswith state commissioners, EPA regionalofficials, and representatives of the Agen-cy for Toxic Substances and Disease Reg-istry. Although this step may initially pro-duce hostility and denial, all of us-government officials and the public-willbe better served in the long run by con-fronting the lack of two-way communica-tion than by spending millions of dollarsthat federal and state officials believe pro-tect public health and quality of life andlocal officials do not. 1]

AcknowledgmentsIwould like tothankmyclleaguesJyce Morris,Frank Popper, and Dona Schneider and healthofficers John Grun ofEdison Township and GlenBelnay of Hilisborouh Township for their com-mentson the instrmnt and a draft of this paper.

References1. Russell M, Colglazier EW, English M. Haz-

ardous Waste Remediation: The Task

Ahead Knoxville, Tenn: Waste Manage-ment Research and Education Institute;1991.

2. National Priorities List, SupplementaryLists and Supporting Materals. Washing-ton, DC: US Environmental ProtectionAgency, Office ofEmergency and RemedialResponse; October 1989.

3. 1989 StatusReport on the Hazardous WasteManagement Program in New Jersey.Trenton, NJ: New Jersey Department ofEnvironmental Protection; 1989.

4. A Management Review of Superfund.Washington, DC: US Environmental Pro-tection Agency; 1989.

5. Chess C, Salomone K, Sandman P. Riskcommunication activities of state healthagencies.AmJPublicHealth. 1991;81:489-491.

6. Hance BJ, Chess C, Sandman P. ImprovingDiagwe with Communitis: A Risk Com-munication Manualfor Govemment. Tren-ton, NJ: New Jersey Department of Envi-ronmental Protection, Division of Scienceand Research; 1988.

7. National Research Council. Improving RiskComrmuniation. Washington, DC: NationalAcademy Press; 1989.

Continuing Female Predominance inDepressive IllnessAndrew C. Leon, PhD, GeraldL Klernan MD, and PriyaWwkramaratne, PhD

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IntrdudionMajor depressive disorder is charac-

terized by periods of dysphoria, fatigue,hopelessness, and sleep and appetite dis-turbances lasting at least 1 week.1 Evi-dence ofhigher rates of depression amongthose born after World War IIwas initiallypresented by Weissman and Myers2 fromthe New Haven Survey and by Robins etal.3 with the Epidemiologic CatchmentArea program data. There are several pos-sible interpretations of this finding. Somesuggest that temporal trends account forthe higher rates of depression.4-11 Othersargue that such findings are artifacts oftheresearch methodology.12"13 If the rateshave, in fact, increased as dramatically assome studies indicate, the public healthimplications could grow as the babyboomers age.

It has been noticed in many preva-lence studies and in the few incidencestudies that rates of depression are higherin females.'4-17 Explanations for these dif-

ferences include genetic, biological, andsociological hypotheses.14,15 Previous re-ports on increasing rates of depressionhave noted female predominance as a gen-eral observation, but the risk has not beenquantified, controlling for temporal ef-fects. However, some observers haveproposed that the gender gap in rates ofdepression is narrowing.18-20 In this pa-per, we examine whether the female pre-dominance persists and whether its mag-

AndrewC. Leon is with the Departnent ofPsy-chiatry at Comell University Medical College,New York, NY. Priya Wickramaratne is withthe College of Physicians and Surgeons of Co-lumbia University, New York, NY. Gerald L.Klermanwas Assocate Chaimana for Researchin the Department of Psychiatry, Comell Uni-versity Medical College, at the time of his deathin April 1992.

Requests for reprints should be sent toAndrew C. Leon, PhD, Department of Psychi-atry, CornellUniversity Medical College, 525E68th St, New York, NY 10021.

This paper was accepted with revisionsDecember 10, 1992.

May 1993, Vol. 83, No. 5

Public Health Briefs

nitude has tapered during the period inwhich the rates have reportedly increased.

MehosThe data come from the baseline in-

terviews ofthe National Institute ofMentalHealth Collaborative Study of the Psycho-biology of Depression.21 The Schedule forAffecfive Disorders and Schizophrenia-Lifetime22was used for Research Diagnos-tic Criteria diagnoses.1 The subjects in-cluded 1137 female and 863 male first-degree relatives of probands with affectivedisorder. Their ages at the time of baselineinterview ranged from 17 to 66 (x = 37.78,SD = 13.97).

Survival analytic techniques wereused to examine the age of onset of majordepressive disorder in the relatives of theprobands. Iniially, proportionswith ama-jor depressive episode by age 35 (comple-ments of the Kaplan-Meier product limitestimates23) were compared across fivebirth cohorts (1915 to 1924, 1925 to 1934,1935 to 1944, 1945 to 1954, and post-1954),stratifiedbygender. Next, the age-specificincidence rates were compared across pe-riod and gender. Finally, the piecewiseconstant hazards model2425 was appliedto estimate the age-specific incidence rates(or hazards) as a function of gender, age,period, and/or cohort. Relative risks (RR)ofthe effects are presented alongwith95%confidence intervals (CI).

ResuksThe prevalence of major depressive

disorder by age 35 is presented in Table 1.(In the latter-born cohorts-those whohad not reached 35 at the time ofinterview-the prevalence by the oldestage is reported.) For women, the preva-lence of depression by age 35 nearly dou-bled in each successive birth cohort, with12% depressed in the 1915 to 1924 cohort

and 61% depressed in the 1945 to 1954cohort. The pattem is similar but less ex-aggerated in men, with rates ranging from6% in the 1915 to 1924 cohort to 31% in the1945 to 1954 cohort.

The age-specific incidence rates arepresented in Table 2, stratified by genderand period. Three apparent risk factors formajor depressive disorder are illustrated.First, women are at increased risk. Sec-ond, the rates appear elevated in the 1960sand 1970s. Finally, regardless of sex orperiod, subjects seemed to be at greatestrisk of a first major depressive episode be-tween ages 16 and 25.

The piecewise exponential modelwas used to test whether the temporalchanges in rates of major depressivedisorder are best explained by birthcohort, period, or age effects. The resultsof the model, presented in Table 3, indi-cate that women had nearly a twofoldincrease in risk of major depressive dis-order (RR = 1.82; 95% CI = 1.51, 2.19).Of the three temporal effects, period wasmost strongly associated with rates ofma-jor depressive disorder (X:ch..ge = 347.1;df = 5; P < .001). The rates were signif-icantly lower in the earlier periods.

Controlling for period, age was nextmost highly associated with rates ofmajordepressive disorder-more so than cohort(age: X2change = 67.95; df = 2; P < .001vs cohort: X2change = 24.95; df = 4;P < .001)-and thus was the other tem-poral effect included in the model. Rela-tive to ages 6 to 15, the risk of a first majordepressive episodewas increasedwell overtwofold during both age intervals 16 to 25and 26 to 35. In addition to the linear in-crease in rates (b = 0.40; exp(b) = 1.49;t = 5.58;P < .001), therewas a significantquadratic effect (b = -0.20; exp(b) = 0.82;t = -6.56;P < .001) indicating thatthe riskacually peaked by ages 16 to 25 and thenstarted to decline. Genderby both age andperiod interactions were also tested, but

neither interaction was statistically signif-icant (X2change = 2.65; df = 2; P = .266and X2change = 1.69; df = 5; P = .890,respecfively).

DiscussionClinicians have noted rising rates of

depression in adolescents and youngadults. Prior epidemiologic work has sup-ported that claim. This study exanined thetemporal trends and gender differences in

American Journal of Public Health 755May 1993, Vol. 83, No. 5

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those trends. Although some reports sug-gest that the female predominance in ratesofdepression is narowing,18-20 our data donot support that. In this family study, thegender gap has not diminihed as the over-all rates have increased over time. Statis-tical tests show additive effects of age, pe-riod, and gender, but no interactions. Thefindings illustrate that women are ahmosttwice as likely to become depressed by age35. The likelihood of a first major depres-sive episode is elevated between ages 16and 25 and was highest during the 1960sand 1970s.

Our findings not only concurwith butalso add to those reported by Lavori etal.,7 who used a different statistical ap-proach to this problem on a subset ofthesedata. The period effect corresponds withtheir results. In addition, we found astrong effect of age and demonstrated theelevated risk ofmajor depressive disorderamong women.

Although the gender, age, and periodof highest risk are demonstrated, theseanalyses do not elucidate the reasons forthe elevated risks. The rate increase cor-responds to a period of increased sub-stance abuse, political turmoil, and socialinstability in the United States. However,without further investigation (e.g., cross-cultural comparisons), the causes will notbe isolated.

There are limitations to our findings.First, these conclusions are based on anenriched sample of relatives of probandswith affective disorder; a sample from thegeneral population would be more gener-alizable. Second, the retrospective life-time diagnoses are not as desirable asthose obtained in a long-term prospectivestudy. However, the diagnoses in thissample have been shown to have the ex-pected patterns of familial aggregation,26prognostic validity,27 and both short- andlong-term reliability.28 -9 Finally, the ap-parent temporal trends could be an artifactof the research methodology; our grouphas elaborated on this elsewhere.9 For in-stance, those born earlier in this centurymay have difficulty recalling depressiveepisodes that occurred many years ago,artificially decreasing the rates in their co-hort. Furthermore, those born after WorldWar II may be more likely to label a prob-lem a "mental disorder." These artifac-tual explanations have credence andshould be examiined empirically. At thesame time, a distinction among the three"real" temporal effects-age, period, andcohort-may focus the search for a patho-genesis of depression. Further research

756 American Journal of Public Health

might examine social and environmentalchanges in the 1960s and 1970s.

The initial public health implicationsof the increased rates ofmajor depressivedisorder have already been manifest inthe increased demand for mental healthservices by adolescents and youngadults. The long-term consequences areunclear. They will depend on the recur-rence and chronicity of the illness inthose already depressed and on the inci-dence rates among the healthy babyboomers as they age. E

AcknowledgmentsThis work was supported, in part, by PublicHealth Service grant UO1 MH43077 and by agrant from the John D. and Catherine T. Mac-Arthur Foundation to Dr. Klerman.

The study, a product of the National In-stitute ofMental Health Collaborative Programon the Psychobiology of Depression-ClinicalStudies, was conducted with the participationof the following investigators: M. B. Keller,MD (chairperson, Boston/Providence); G. L.Klerman, MD (cochairman); J. Maser, PhD(Washington, DC); P. W. Lavori, PhD, andM. T. Shea, PhD (Boston/Providence); J. A.Fawcett, MD, W. A. Scheftner, MD, and M.Young, PhD (Chicago); W. Coryell, MD, and J.Haley (Iowa City); J. Endicott, PhD, and J.Loth,MSW(New York); and J. Rice, PhD, andT. Reich, MD (St. Louis). Other contributorsinclude N. C. Andreasen, MD, P. J. Clayton,MD, J. Croughan, MD, R. M. A. Hirschfeld,MD, M. M. Katz, PhD, E. Robins, MD, R. W.Shapiro, MD, R. L. Spitzer, MD, and G.Winokur.

This manuscript has been reviewedby thePublication Committee of the CollaborativeProgram and has its endorsement.

References1. Spitzer R, Endicott J, Robins E. Research

diagnostic criteria: Rationale and reliabil-ity.Arch GenPsychiatry. 1978;35:773-782.

2. Weissman MM, Myers JK. Affective dis-orders in aUS urban community: the use ofthe research diagnostic criteria in an epide-miological survey. Arch Gen Psychiatry.1978;35:1304-1311.

3. RobinsL, HelzerJE, Weissman MM, et al.Lifetime prevalence of specific psychiatricdisorders in three sites. Arch Gen Psychi-atry. 1984;41:949-958.

4. Hagnell 0, Lanke J, Rorsman B, Ojesjo L.Arewe entering an age of melancholy? De-pressive illnesses in a prospective epidemi-ological study over 25 years: the LundbyStudy Sweden. PsycholMed 1982;12:279-289.

5. Klerman GL, Lavori PW, Rice J, Reich T.Birth cohort trends in rates of major de-pressive disorder in relatives of patientswith affective disorder. Arch Gen Psychi-atry. 1985;42:689-693.

6. Lavori PW, Klerman GL, Keller MB, Re-ich T, Rice J, Endicott J. Age-period-ohort analysis of secular trends in onset ofmajor depression: findings in siblings of pa-tients with major affective disorder. JPsy-chiatrRes. 1987;21:23-35.

7. Klerman GL. The current age of youthfulmelancholia: evidence for increase in de-pression among adolescents and youngadults. BrJPsychiatiy. 1988;152:4-14.

8. Klerman GL, Weissman MM. Increasingrates of depression. JAMA. 1989;261:2229-2235.

9. Wickramaratne PJ, Weissman MM, LeafPJ, Holford TR. Age, period and cohorteffects on the risk of major depression: re-sults from five United States communities.J Cin EpidemioL 1989;42:333-343.

10. Warshaw M, Klerman GL, Lavori PW.The use of conditional probabilities to ex-amine age-period-cohort data: further evi-dence for a period effect in major depres-sive disorder. JAffective Disord 1991;23:119-129.

11. Cross-National Collaborative Group. Thechanging rate of major depression: cross-national comparisons. JAMA. 1992;268:3098-3105.

12. Srole L, Fischer AK. The Midtown Man-hattan longitudinal study vs "The MentalParadise Lost" doctrine: a controversyjoined.Arch GenPsychiatry. 1980;37:209-221.

13. Hasin D, Link B. Age and recognition ofdepression: implications for a cohort effectin major depression. Psychol Med 1988;18:683-688.

14. Weissman MM, Klerman GL. Sex differ-ences and the epidemiology of depression.Arch Gen Psychiat,y. 1977;34:98-111.

15. Weissman MM, Klerman GL. Gender anddepression. Trends Neurosci 1985;8:416-420.

16. Young MA, Scheftner WA, Fawcett J, K1-erman GL. Gender differences in the clin-ical features of unipolar major depressivedisorder. JNerv Ment Dis. 1990;178:200-203.

17. Coryell W, Keller M, Endicott J. Majordepression in a non-clinical sample: demo-graphic and clinical risk factors for first on-set. Arch Gen Psychiatry. 1992;49:117-125.

18. MurphyJM. Trends in depression and anx-iety: men and women. Acta PsychiatrScand- 1986;73:113-127.

19. Kessler RC. Sex differences in psychiatrichelp-seeking: evidence from four large-scale surveys. J Health Soc Behav. 1981;22:49-64.

20. Eaton WW, Kramer M, Anthony JC, Dry-man A, Shapiro S, Locke BZ. The inci-dence of specific DIS/DSM-III mental dis-order: data from the NIMH EpidemiologicCatchment Area program. Acta PsychiatrScand 1989;79:163-178.

21. Katz MM, Klerman GL. Introduction:overview of the clinical studies program.Am JPsychiatry. 1979;136:49-51.

22. Endicott J, Spitzer R. A diagnostic inter-view: Schedule for Affective Disorders andSchizophrenia.Arch GenPsychiatiy. 1978;35:837-844.

23. Kaplan EL, Meier P. Nonparametric esti-mation from incomplete observations. JAm StatAssoc. 1958;53:457-481.

24. Holford TR. Life tables with concomitantinformation. Biometrics. 1976;32:587-597.

25. Holford TR. The estimation of age, periodand cohort effects from vital rates. Biomet-rics. 1983;39:311-324.

26. Andreasen NC, Rice J, Endicott J, Coiyell

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W, Grove WM, Reich T. Familial rates ofaffective disorder: a report from the NIMHCollaborative Study.Arch GenPsychiatry.1987;44:461-469.

27. Coryell W, Endicott J, Keller MB. Predic-tors of relapse into major depression in a

nonclinical population. Am J Psychiaty.1991;148:1353-1358.

28. Andreasen NC, Grove WM, Shapiro RW,Keller MB, Hirschfeld RMA, MacDon-ald-Scott P. Reliability of lifetime diagno-sis: a multicenter collaborative perspec-

Public Health Briefs

tive. Arch Gen Psychiat,y. 1981;38:400-405.

29. Rice JP, Rochberg N, Endicott J, LavoriPW, Miller C. The stability of psychiatricdiagnoses: an application to the affectivedisorders. Arch Gen Psychiaty. In press.

1~~ ~I .. I

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May 1993, Vol. 83, No. 5 American Journal of Public Health 757