Familial insulin-dependent diabetes mellitus (IDDM ...

Familial insulin-dependent diabetes mellitus (IDDM)epidemiology: standardization of data for theDIAMOND Project*The WHO Multinational Project for Childhood Diabetes Group1

The WHO Multinational Project for Childhood Diabetes, known as the DIAMOND Project, has beenresponsible for establishing insulin-dependent diabetes mellitus (IDDM) registries and for carrying outdiabetes incidence studies, descriptive epidemiological research, and analytical investigations which arebeing used to test specific hypotheses regarding the etiology of the disease. Standardized epidemiologicaldata are being collected from countries around the world, permitting international comparisons betweenregistries. Multinational studies are also beginning to investigate the potential genetic determinants of thedisease, and are contributing to the development of familial IDDM epidemiology worldwide. The develop-ment of standards for data collection of IDDM family histories is important for multinational studies ofIDDM recurrence risks in families, descriptive analyses of patterns of familial aggregation, and compara-tive analytical investigations of specific etiological determinants of IDDM in relatives. These activities arebeing implemented through the DIAMOND Project.

Introduction

Research by IDDM registriesThe establishment of standardized population-basedregistries has produced data which show that theincidence of insulin-dependent diabetes mellitus(IDDM) varies widely between racial groups andcountries (1-3). Children living in Finland, forexample, have more than a 30-fold increase in theirrisk of developing the disease compared with child-

ren living in the Republic of Korea or Japan (Fig. 1).Racial variations in risk within a population havealso been observed, with a higher IDDM incidencerate among Whites than Blacks or Hispanics livingin the same geographically-defined area (Table 1).

Besides reporting the global patterns of inci-dence, these IDDM registries have been utilized forevaluating the epidemiology of the disease (2-4). Acomparative study in the USA (Allegheny County,PA) and Japan shows that despite a 20-fold differ-ence in IDDM incidence, the epidemiological pat-

* This article was prepared by Dr J. S. Dorman, WHO Collabo-rating Center for Diabetes Registries and Training, Department ofEpidemiology, Graduate School of Public Health, University ofPittsburgh, Pittsburgh, PA 15261, USA. Requests for reprintsshould be sent to this address.

1 The participating countries and members of the group were:Algeria (Oran), K. Bessaoud; Argentina (Buenos Aires), M. deSereday, M. Marti; Austria (Vienna), E. Schober; Brazil (SaoPaulo), L. Franco, C. Negrato, E. Russo, M. Schmidt, M. Vivolo;Canada (Montreal), E. Colle, A. Schiffrin, J. Siemiatycki; and(Nova Scotia), M.H. Tan, C. Wornell; Chile (Santiago), E. Car-rasco, G. Lopez, M. Garcia de los Rios; Cuba (Havana), 0. Mateode Acosta, 0. Diaz-Diaz, M. Vera, T. Norot, A. Uriate; DominicanRepublic (Santo Domingo), A. Selman-Geara; Egypt (Cairo), N.Hashem, R. Shawki, S. Eid, S. Taha; Finland (Helsinki), A.Reunanen, J. Tuomilehto, E. Tuomilehto-Wolf; Germany(Frankfurt), B. Boehm, C. Rosak, K. Schmidt; Hungary (Pecs), G.Soltesz and the Hungarian Childhood Diabetes EpidemiologyStudy Group; India (Madras), A. Ramachandran, V. Mohan, C.Snehalatha, M. Viswanathan; and (New Delhi), N.P.S. Verma, A.Goel; Italy (Cagliari), S. Muntoni, P. Masile, M. Silvetti, M.Songini, P. Tronci; (Chieti), F. Chiarelli; (Milan), G. Chiumello, F.Meschi, E. Bognetti; (Pavia), M. Tenconi, G. DeVoti, M. Martinetti,R. Lorini, F. Severi; (Rome), P. Pozzilli, M. Boccuni, R. Buzzetti,

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L. Sebastiani, N. Visalli; and (Torino), G. Pagano, G. Bruno, F.Merletti, E. Pisu; Japan (Hokkaido), N. Matsuura, K. Fujieda, A.Okuno, K. Ooyanagi, K. Yano; and (Okinawa), G. Mimura, H.Futenma, S. Higa, K. Murakami, M. Nagayoshi; Kuwait (Safat), M.Khogali, N. Abdella, K. Gumaa, A. Shaltout; New Zealand(Auckland), R. Elliott; and (Christchurch), R. Scott; Norway(Oslo), G. Joner, 0. Sovik; Paraguay (Asuncion), J. Jimenez, C.Palacios, F. Canete, J. Vera, R. Almiron; Poland (Poznan), M.Rewers, P. Fichna, M. Walczak, M. Jozwiak, D. Woznicka;Romania (Bucharest), C. lonescu-Tirgoviste, D. Cheta; SpAin(Barcelona), A. Goday, C. Castell, R. Gomis, G. Lloveras; and(Madrid), M. Serrano-Rios; Sudan (Khartoum), A. Elamin, K.Eltayeb, M. Omer, K. Zein; Sweden (Stockholm), G. Dahlqvist;United Kingdom (Leicester, England), A. Burden, M. Boddington,M. Burden, S. Sheera; and (Belfast, Northern Ireland), C. Pat-terson, D. Hadden; USA (Alabama, Birmingham), J. Roseman, R.Acton, R. Go, L. Wagenknecht; (Colorado, Denver), R. Hamman,J. Kostraba; (Florida, Tampa), J. Malone, P. Leaverton, D.Schocken; (Georgia, Atlanta), T. Hodge; (Illinois, Chicago), R.Lipton; (Minnesota, Rochester), D. Ballard, P. Palumbo; (NorthDakota, Grand Forks), J. Brosseau, D. Sumbureru;(Pennsylvania, Pittsburgh), J. Dorman, R. LaPorte, C. Moy, M.Trucco; and (Puerto Rico), T. Frazer de Llado; USSR (Estonia), T.Podar, B. Adojaan, 1. Kalits; (Lithuania), V. Grabauskas, A.Norkus, Z. Padaiga, R. Preiksa, B. Urbonaite; and (Novosibirsk),E. Shubnikov, L. Kalashnikova; and Yugoslavia (Ljubljana), C.Krzisnik. WHO Secretariat (Geneva, Switzerland), H. King.

Bulletin of the World Health Organization, 69 (6): 767-777 (1991) C, World Health Organization 1991 767

WHO Multinational Project for Childhood Diabetes Group

Fig. 1. Age-adjusted IDDM Incidence rates (per 100000population). Source: reference 3.

Sweden

Norway

USA: N. Dakota

USA: Alabama. Whites

New Zealand

Netherlands I

Poland

USA: Alabama, Blacks

Japan

Incidence rate

terns for the two populations are virtually identical(4), which suggests that the marked difference inIDDM incidence is due to variation in the preva-lence of common etiological risk factors, eithergenetic or environmental, in the population. Compa-rative descriptive epidemiological studies have led tohypotheses on the causes of the marked geographicaland racial differences in IDDM incidence. It hasrecently been proposed that population variation inthe prevalence of IDDM susceptibility genes, ratherthan differences in environmental factors, is theprimary determinant of the worldwide patterns ofdisease (5).

Table 1: Age-adjusted (0-14 years) Incidence of IDDM(per 100000 population) by ethnic group, USA"

Ethnic group

Registry White Black Oriental Hispanic

Colorado 16.4 9.7(1978-83) (15.-17.8)b (7.4-12.4)

Pennsylvania, 16.2 11.8Allegheny (14.1-18.4) (7.9-17.2)County(1978-83)

Alabama, 16.9 4.4Jefferson (13.4-21.4) (2.3-7.5)County(1979-83)

California, 13.8 3.3 6.4 4.1San Diego (9.8-18.9) (0.4-11.9) (1.3-18.7) (1.3-9.6)(1978-80)

a Source: reference3.b Figures in parentheses are the 95%-confidence intervals for theincidence rates.

The next step is to test these etiological hypoth-eses (6). This is a primary objective of the WHOMultinational Project for Childhood Diabetes (7),also known as the DIAMOND Project. The initi-ation of analytic epidemiological studies requires anunderstanding of the factors that contribute to theoccurrence of disease within specific populations.Although the environmental determinants of IDDMremain unclear, much is known about genetic sus-ceptibilities to the disease.

Genetic factors and IDDMIndependent of the search for specific IDDM suscep-tibility markers, descriptive studies of the relatives ofindividuals with the disease demonstrated familialaggregation of IDDM (8-15), but attempts to definea specific mode of inheritance have been unsuc-cessful. It was concluded that an underlying suscepti-bility to the disease was inherited, and that ingenetically predisposed individuals, the interactionbetween environmental and immunological factorsled to the development ofIDDM (16-18).

HLA (human leukocyte antigen) associationstudies (19, 20), as well as linkage studies in families(21-23), confirm that IDDM susceptibility genes arelocated within the HLA region of chromosome 6.With advances in molecular biology, it has becomeapparent that HLA-DQ locus polymorphisms, par-ticularly those at position 57 of the beta chain, playa functional role in determining IDDM susceptibilityand are strongly associated with the disease (24, 25).Recent data suggest that the proposed hypothesisregarding the contribution of the DQ beta polymor-phisms to the worldwide patterns of IDDM inci-dence is correct, with a direct relationship betweenthe frequency of this genetic marker and disease risk(5).

In addition to the presence of IDDM suscepti-bility genes, potential environmental risk factors arelikely to cluster in the families of affected individuals.Familial IDDM epidemiology is currently expandingbeyond descriptive evaluations to include molecularassessments of potential genetic, environmental, andother epidemiological risk factors in first-degree rela-tives. These analytical studies permit the testing ofspecific hypotheses regarding the causes of IDDMclustering within families. When conducted in inci-dence cohorts using epidemiological methods, suchinvestigations provide estimates of the absolute riskof the disease for relatives with specific host-environmental exposures (26). This illustrates theimportance of a population-based approach forfurther research in familial IDDM epidemiology.

The establishment of IDDM incidence registriesin countries across the world, through theDIAMOND Project, provides an excellent founda-

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Familial Insulin-dependent diabetes mellitus epidemiology

tion for the development of such research worldwide.Standardization is an essential component of inter-national epidemiological studies (1-3, 27), forwithout standards, accurate geographical and racialcomparisons cannot be achieved. This paper dis-cusses the applications of IDDM family historyinformation on a national and multinational level,describes the importance of standard family historydata collection and the specific areas which requirestandardization, and presents recommendations forthe implementation of these standards through theDIAMOND Project.

Epidemiology and data collection

Development of familial IDDM epidemiologyWithin countries, family history information willpermit (1) estimation of IDDM recurrence risks infamilies, (2) assessments of the familial aggregation ofthe disease, (3) evaluations of the epidemiology ofIDDM in family members, and (4) identification ofprobands and families for genetic marker studies.When standard family history data are obtainedacross populations, comparative descriptive andanalytical studies of familial IDDM epidemiologycan be conducted. This information will greatly con-tribute to our knowledge of host-environmentalinteractions in the etiology of IDDM, and will leadto a better understanding of the determinants of theworldwide distribution of the disease.

IDDM recurrence risks in families. Table 2 shows thatsiblings, parents and children of a diabetic probandhave higher IDDM risks than unrelated individualsin the general population, approximating 3% to 10%by the age of 30 years (10-13, 28, 29). The data pre-sented are not directly comparable, primarily

Table 2: Risk of developing IDDM for relatives of anIDDM proband

Relationship to Cumulativeproband risk Reference

Parents:Denmark 1.1% to age 35 yrs 10USA 2.6% to age 40 yrs 12Germany 2.2% to age 80 yrs 29

Siblings:Denmark 5.1% to age 20 yrs 10USA 3.3% to age 20 yrs 12USA 5.5% to age 40 yrs 11Germany 6.9% to age 80 yrs 29India 1.5% to age 20 yrs 13

Children:Denmark 2.8% to age 20 yrs 10Germany 5.6% to age 80 yrs 29

because of methodological differences. Most of thestudy populations consisted of patients identifiedfrom hospitals or diabetes clinics (10-14, 28, 29).Owing to a potential referral bias, multiple-case fam-ilies were likely to be overrepresented in thesecohorts. This may have increased the IDDM riskestimates for family members above those obtainedfrom more representative groups. Furthermore, defi-nitions of diabetes among family members variedconsiderably. Several investigations did not dis-tinguish insulin-dependent from noninsulin-dependent diabetes mellitus (NIDDM), and othersdefined diabetes in terms of current therapy, but didnot consider the age at onset of the disease. Therewere also inconsistencies in the methods employedfor data collection. Sources included hospital andclinic records, personal interviews with the probandsand/or family members, and self-report question-naires. Because standard data were not obtained in auniform manner from representative populations,accurate between-population comparisons of IDDMrisks to family members could not be made.

Most of the studies in Table 2 represent Cauca-sian populations from areas with similar incidencerates. There is a paucity of information for otherracial groups and from populations with a very highor very low disease incidence. Despite geographicaldifferences in the prevalence of IDDM susceptibilitygenes (5), the worldwide variation in IDDM risk torelatives may be less dramatic than that observed forthe general population. First-degree relatives fromvarious nationalities are likely to be genetically morehomogeneous and to share exposure to environ-mental risk factors more frequently than unrelatedindividuals in the general population. Thus, multi-national comparisons of IDDM risks to familymembers may reveal less variability across countriesthan the reported 50-fold difference in populationincidence rates. It is only through the collection ofstandard family history data that accurate interna-tional comparisons in IDDM recurrence risks can bemade.

Familal aggregation of IDDM. One of the most intrigu-ing patterns of familial aggregation of IDDM is thesex difference in the prevalence of parental diabetes.Diabetic children from families with an IDDMparent (i.e., parent-offspring families) are signifi-cantly more likely to have an affected father than anIDDM mother (28, 29). Although this observationhas been reported by a number of independentstudies (Table 3), the mechanism by which paternalIDDM is more frequently transmitted remainspoorly understood. Several possible explanationshave been proposed, including an increase in sponta-neous abortion of susceptible fetuses by IDDM

WHO Bulletin OMS. Vol 69 1991 769


Table 3: Risk of developing IDDM for children of IDDMmothers and fathers

Children of CumulativeIDDM parents risk Reference

Father:Denmark 4.2% to age 20 yrs 28USA 6.1% to age 20 yrs 28Germany 33.4% to age 80 yrs 29

Mother:Denmark 1.8% to age 20 yrs 28USA 1.3% to age 20 yrs 28Germany 4.4% to age 80 yrs 29

mothers (28), maternal immunological tolerance offetuses to autoantigens of the beta cells (30), anincrease in the paternal transmission of HLA suscep-tibility genes (31, 32), and genomic imprinting (33-35).

Most of the information regarding sex differ-ences in parental IDDM has been retrospectivelyobtained from studies of newly diagnosed Caucasianchildren. Comparable data are needed to determinewhether similar findings would be observed for non-Caucasian populations or in countries which vary inoverall disease incidence. There have been few pro-spective studies of children born to individuals withIDDM (28, 30, 36). Such evaluations are required forprecise risk estimates and accurate comparisons ofthe incidence of IDDM among children of diabeticfathers versus mothers. Hypotheses regarding the sexdifference in parental IDDM can be tested by ana-lysing standardized family history data collectedfrom IDDM registries extending back to the 1950sand 1960s.

Epidemiology of IDDM In famiiy members. The epidemi-ology of IDDM in family members has been investi-gated in several populations. Characteristicsincluding a higher birth order (37, 38) and oldermaternal age (38) have been shown to be associatedwith an increased IDDM risk among siblings. Thesedescriptive studies have contributed to currenthypotheses regarding possible host-environmentalinteractions in familial IDDM. To directly test thesehypotheses, analytical family studies are now includ-ing determinations of specific genetic markers (i.e.,HLA-DQ beta polymorphisms and/or HLA hap-lotype sharing), as well as exposure to potentialenvironmental risk factors (i.e., breast-feeding,viruses, etc.) in first-degree relatives. When the inci-dence of IDDM among family members is alsoknown, it is possible to estimate the absolute risk ofdisease for relatives with specific risk factors (26).With standardized family history data, analyticalstudies can be conducted across populations, provid-

ing assessments of potential determinants of geo-graphical differences in IDDM recurrence risks.

Temporal increases in incidence and 'epidemics'of IDDM have been reported in several Europeancountries (39-41). However, it is not known whethersimilar temporal increases in risk occurred amongfamily members. Temporal trends in the risk to rela-tives could be due to a greater clustering of environ-mental diabetogenic factors within families orpossible host-environmental interactions. One mayalso predict that during periods of increasing popu-lation incidence, the interval between the onset ofdisease in the proband and other family membersmay be shorter than that observed during periods ofmore stable incidence rates. An evaluation of thetemporal changes in familial IDDM incidence wouldprovide important insights as to the nature of theenvironmental determinants of the disease and theirinteraction with host susceptibility.

Identifying families for genetic marker studies. The col-lection of family history data is also important foridentifying probands and informative simplex andmultiplex families for serological and moleculargenetic studies of the etiology of IDDM. The ration-ale and methods for standardizing internationalcase-control and family studies of host susceptibilityare important issues that will require careful con-sideration and planning to assure comparabilityacross populations.

Collection of standardized family historyInformationThe development of standards for the collection andanalyses of family history data must be similar tothose developed for the standardized IDDM inci-dence registries (27). The core information should beminimal and easy to ascertain so that the standardsare applicable in developed and developing countriesacross the world. To achieve these goals, standardsare needed for: (1) definition of the family structure,(2) definition of core variables to determine the pre-sence of diabetes in all family members, (3) methodsof family history data collection, and (4) data storageand analyses. Through the DIAMOND Project, itwill be possible to implement such standards anddevelop familial IDDM epidemiology on a multi-national level.

Determining the family structure. As with the evolutionof population-based registry research, the develop-ment of familial IDDM epidemiology has its founda-tion in determining the number of family memberswith the disease (numerator) and evaluating thepopulation of first-degree relatives at risk



(denominator). Thus, it is necessary to obtain a fullfamily pedigree to determine the structure of thenuclear family. This information is critical for accu-rate estimations of IDDM recurrence risks ordescriptive analyses of familial IDDM aggregation.

In some of the developing countries, it may notbe possible to identify all individuals who arebiologically-related to the proband. Geographicaldifferences in cultural practices and family roles maylead to biased evaluations of family structure. Situ-ations such as divorce and death, including theoccurrence of miscarriages and stillbirths, may alsocontribute to inaccuracies in defining the populationof first-degree relatives at risk. Obtaining accuratefamily history data in developed countries may alsobe difficult and requires special skills on the part ofthe interviewer. Given the personal nature of thesedata, the respondent must feel relaxed and assuredthat all family history information will be completelyconfidential. This will facilitate an accurate assess-ment of the family structure. Such issues must beaddressed in each population prior to beginningdata collection.

Definition of core varlables. One of the most impor-tant core variables for the assessment of diabetes infamily members is the definition of the disease. Apractical and accurate definition of IDDM wasdeveloped for standardized population-based inci-dence registries (1-3). For purposes of registeringchildhood IDDM cases (age, 0-14 years), it wasagreed that the disease definition should be based ona confirmed diagnosis by a physician, and thepatient should be: (i) aged less than 15 years at thedisease's onset, (ii) a resident of the defined targetpopulation for the registry at the time of diagnosis,and (iii) on insulin at the time of hospital discharge(1-3, 27). This information could be accuratelyobtained from the medical records of patients, easilyverified, and standardized in countries around theworld.

A similar approach is required for internationalstudies of familial diabetes. Since laboratory or clini-cal facilities may not be available in all populations,the only feasible way of assessing the occurrence ofdiabetes in family members is to utilize a set of corevariables, to be obtained by survey, from cases iden-tified from population-based registries.

The core data required for evaluating familialIDDM are outlined in Table 4. These items must beobtained for each first-degree relative (i.e., parents,siblings and children) in the family and include: (1)sex, (2) living status, (3) date of birth, (4) if deceased,information concerning cause, date and place ofdeath, and (5) diabetes status; in addition, (6) themonth and year (or age) at diagnosis, and (7) the

Table 4: Core family history data required for compara-tive genetic epidemiological research

For all first-degree relatives:-Sex-Whether alive or dead-Date of birth-If deceased, the cause, date and

place of death-Diabetes status

For diabetic first-degree relatives:-Month/year (or age) at diagnosis-Month/year (or age) when continuous

insulin treatment was started

month and year (or age) when continuous insulintreatment was started should be obtained for allindividuals with diabetes. By utilizing core variables,such as age at diagnosis and type of diabetestherapy, it is possible to assess the occurrence offamilial IDDM by questionnaire.

Although the age-at-onset for registering allchildhood IDDM cases in a community was fixed atless than 15 years, we can consider a less conserva-tive definition to distinguish parental IDDM fromNIDDM. For example, individuals who were under35 years old at disease onset and were placed oninsulin therapy at diagnosis are most likely to beinsulin-dependent. To ensure the accuracy of thisdefinition, these data will be verified with hospitaland physician records, and then standardized acrosspopulations.

The DIAMOND Project's international com-parisons of IDDM risks to family members focusexclusively on the first-degree relatives of probands.However, extended family history data on theoccurrence of diabetes in maternal and paternalgrandparents, aunts, uncles and cousins may also beobtained if more in-depth pedigree analyses aredesired by individual centres.

Methods of data collectlon. Once the standard corevariables have been defined, family history informa-tion can be collected by survey, which is the onlypractical approach to make international compari-sons. By standardizing the core variables, asdescribed above, it is possible to assess theoccurrence of familial IDDM using questionnaires.A standardized form, which can be easily adapted,will facilitate the collection of family history coredata for the DIAMOND Project. An example ofsuch forms is given in the Annex. This instrumentcan be modified so that it is convenient for data col-lection by individual centres and for comparison ofdata between populations.

There are several methods of administering thequestionnaire to probands and/or family members



Table 5: WHO Multinational Project for Childhood Diabetes: assessment of family history Information from 42 registriesIn 26 countries

Method of data Information Method of data InformationRegistry collection obtained Registry collection obtained

Argentina, Buenos SurveyAires

Austria, Vienna Interview/medicalrecords

Brazil, Sao Paulo Survey

Canada, Montreal Interview

Chile, Santiago Interview/medicalrecords

Finland, Helsinki Survey/interview

Egypt, Cairo Interview/medicalrecords

Germany, Frankfurt Interview/medicalrecords

Hungary, Pecs Survey

India: Madras Interview

New Delhi Interview

Italy: Cagliari Medical records

Milan Interview

Pavia Interview

Rome Medical records

Japan: Hokkaido Survey

Okinawa Interview/medicalrecords

Kuwait, Safat Interview

New Zealand: Interview/medicalAuckland recordsChristchurch Survey/interview

medical recordsNorway, Oslo Medical records

Most core data:sibs, parents

Core data: sibs,parents

Core data: sibs,parents, children

Diabetes status:sibs, parents













Core diabetes data:sibs, parents

Core data: sibs,children





Paraguay,Asuncion

Poland, Poznan

Romania,Bucharest

Spain: Barcelona

Madrid

Sudan, Khartoum

Sweden,Stockholm

United Kingdom:Leicester,England

Belfast, N. Ireland

USA: Alabama,Birmingham

Colorado,Denver

Florida, Tampa

Minnesota,Olmsted County

North Dakota,Grand Forks

Pennsylvania,AlleghenyCounty

Puerto Rico

USSR: Estonia

Lithuania

Interview/medicalrecords


Survey

Medical records

Survey/interview

Interview

Survey

Survey/interview

Medical records

Interview

Survey/interview

Survey/medicalrecords

Survey/interview/medical records

Survey/interview

Survey/interview


Survey

Interview

Novosibirsk Survey

Yugoslavia,Ljubljana

Survey





















which warrant consideration. The form shown in theAnnex was designed so that it could be completed byIDDM cases who were aged 16 years and over, or bytheir parents or guardians if the proband was under16 years. The form can be mailed to each registeredcase, completed at home and returned in a stampedenvelope. This approach provides the participantand his/her family an opportunity and time to accu-rately recall or look for information regarding datesof birth, dates of diabetes onset, etc. concerningother family members. A disadvantage of thismethod of data collection is that many individualswill not respond or return the survey form without a

reminder by the research centre. Thus, to obtainfamily history information from more than 80% ofthe registered cases, several reminders are generallyrequired for approximately one-half of the targetpopulation.

To improve the response rate, family historyinformation can also be obtained by telephone inter-views with the proband or his/her first-degree rela-tive. This approach generally provides a highresponse rate, but the data may be less accurateowing to memory biases. A combination of thesemethods will facilitate complete data collection indeveloped countries with good mail and phone


Algeria, Oran Survey

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systems. These approaches are also valuable forregistries with retrospective case ascertainment.However, they may not be useful in developingcountries or for prospective registries.

Family history data may also be obtained fromshort personal interviews at the time of first hospitaladmission or during diabetes clinic appointments.This approach may be most useful in populationsemploying prospective case registration. Interviewsare also an ideal method for data collection indeveloping countries where many individuals are notaccessible by mail or phone.

Using these approaches, family history informa-tion has already been successfully obtained from anumber of the population-based IDDM incidenceregistries which are part of the DIAMOND Project(Table 5). The survey instruments varied acrosspopulations and the core information was not stan-dardized. Thus, it was not possible to accuratelycompare the existing data. However, the similaritiesin the approaches employed by various countriesindicate that the use of standards for family historydata collection is feasible for international collabo-rative research.

Data storage and analyses. Irrespective of the methodof obtaining family history information, the collecteddata for comparative analyses must be computerizedin a standardized manner. In particular, the coredata for each first-degree relative must be entered asa separate record. Identification numbers must bedefined to distinguish between families (family identi-fication numbers), diabetic probands (case identifica-tion numbers), and individuals within families(member identification numbers) and must beincluded with the core data for that individual. Anexample of a numerical coding system which hasbeen employed to identify specific relatives in familydata sets is also given in the Annex.

Standards for data storage will also facilitate thesharing of computer analyses programs designed toestimate the recurrence risks to relatives, etc. Suchprograms are being developed for the DIAMONDProject using the computer software dBASE IV.Standardized dBASE database management systemsfor family history data and analyses will be distrib-uted to all DIAMOND participating centres. Theseprograms will permit the identification of singleversus multiple IDDM case families, and distinguishbetween those with affected siblings and parents.Secondly, programs for the analyses of familialIDDM aggregation will be included. This will permita description of unaffected and affected relatives,characterizing their age at onset of diabetes, sex,birth order, living status of relatives, etc. Thirdly,life-table analyses programs will estimate IDDM

recurrence risks in siblings, parents and children.Finally, these programs will be linked to those beingestablished for the DIAMOND incidence studies,providing comparisons between the IDDM inci-dence rates among relatives with the risk estimatesfor the general population. The distribution of theseprograms through the DIAMOND Project willensure that family history data can be analysed inthe same manner across populations.

ConclusionsThe next generation of IDDM research is nowbeginning with the development of familial IDDMepidemiology on a national and multinational level.This article has focused on standardization ofmethods for data collection concerning IDDMfamily histories. The development of these standardswill greatly facilitate international collaborativeresearch in areas where IDDM incidence registriesare established. Population-based epidemiologicalstudies are essential to our understanding of the con-tribution of familial and genetic factors to the globalpatterns of IDDM incidence. In addition, they willpermit investigators to develop hypotheses regardingpossible environmental factors and even preventivestrategies, which is the ultimate objective of theWHO Multinational Project for Childhood Dia-betes.

AnnexStandardization of core Information on diabetesfamily historiesAlthough core variables (Table 4) from studies of thefamilial risk of diabetes across populations can becollected in any format, it is important for compara-tive studies that they accurately represent the statusof all first-degree relatives in the family. Withoutcomplete data for the entire family, it is not possibleto identify the number of non-diabetic relatives,which prohibits the calculation of the overall andage-specific familial risk of IDDM. The two exam-ples of survey forms for use in the DIAMONDProject to assess the occurrence of IDDM in parents,siblings, and children (see p. 774) may be translatedor modified according to the specific needs of eachregistry.

The data to be collected as core information forthe entire nuclear family of the diabetic index casemust include the following: sex; whether alive ordeceased; date of birth; if deceased, the cause, date(or age) and place of death; diabetes status (diabeticby WHO criteria or non-diabetic); age diabetes diag-nosed; use of insulin for treatment of diabetes (yes or


INFORMATION ON FAMILY OF DIABETIC

I.D. #: DATE:

THIS FORM PERTAINS TO THE DIABETIC'S IMMEDIATE FAMILY. PLEASE COMPLETE ALL INFORMATION FOR THE MOTHER, FATHER,BROTHERS, AND SISTERS OF (BEGINNING WITH THE OLDEST AND ENDING WITH THE YOUNGEST). PLEASE INCLUDEIN THE LIST OF SIBLINGS, AS WELL AS HALF-BROTHERS AND SISTERS, ADOPTED BROTHERS AND SISTERS, AND BROTHERS AND SISTERSWHO ARE DECEASED. IF THERE ARE ANY ADDITIONAL SIBLINGS, PLEASE LIST THEM ON A SEPARATE SHEET.

MONTH/YEARCURRENT IF DECEASED, MONTH/YEAR (OR AGE)

NAME AGE INDICATE YEAR (OR AGE) CONTINUOUSDATE OF (OR AGE AND CAUSE OF USE DIABETES INSULIN

(PLEASE INCLUDE MARRIED NAMES) SEX BIRTH ALIVE? DECEASED) DEATH DIABETIC? INSULIN? DIAGNOSED TREATMENTMOTHER

FATHER

OLDEST SIBLING

2ND SIBLING

3RD SIBLING

IF ANY OF THE INDIVIDUALS LISTED ABOVE ARE HALF- OR STEP- BROTHERS AND SISTERS, OR ADOPTED, PLEASE LIST THEIR NAMES ANDSPECIFY THEIR RELATIONSHIP TO THE DIABETIC. FOR HALF- BROTHERS AND SISTERS, INDICATE WHETHER THE MOTHER OR THE FATHER ISTHE COMMON PARENT.

INFORMANT: SOURCE OF INFORMATION: PERSONAL INTERVIEW _ TELEPHONE INTERVIEWMAILED SURVEY

INFORMATION ON FAMILY OF DIABETIC

I.D. #: DATE:

THIS FORM PERTAINS TO THE DIABETIC'S IMMEDIATE FAMILY. PLEASE COMPLETE ALL INFORMATION FOR THE SPOUSE AND CHILDRENOF _ _ (BEGINNING WITH THE OLDEST CHILD AND ENDING WITH THE YOUNGEST). PLEASE INCLUDE ANY ADOPTED CHILDREN,MISCARRIAGES, STILLBIRTHS, ABORTIONS, AND CHILDREN WHO MAY BE DECEASED. IF THERE ARE ANY ADDITIONAL CHILDREN, PLEASELIST THEM ON A SEPARATE SHEET.

MONTH/YEARCURRENT IF DECEASED, MONTH/YEAR (OR AGE)

NAME AGE INDICATE YEAR (OR AGE) CONTINUOUSDATE OF (OR AGE AND CAUSE OF USE DIABETES INSULIN

(PLEASE INCLUDE MARRIED NAMES) SEX BIRTH ALIVE? DECEASED) DEATH DIABETIC? INSULIN? DIAGNOSEED TREATMENTSPOUSE

OLDEST CHILD

2ND CHILD

3RD CHILD

4-- 4 - 4- 4 4- I4

± 1 +

- 4 4 4 I-I

+i + + 4 4- 4 .

IF ANY OF THE INDIVIDUALS LISTED ABOVE ARE ADOPTED, OR ARE STEP- CHILDREN, PLEASE LIST THEIR NAMES.

INFORMANT: SOURCE OF INFORMATION: PERSONAL INTERVIEW _ TELEPHONE INTERVIEWMAILED SURVEY

Familial insulln-dependent diabetes mellitus epidemiology

no); and age when insulin was first used (for insulin-using diabetics).

With the survey forms, the data are collected forthe diabetic index case, his/her natural parents, andeach sibling (beginning with the oldest, ending withthe youngest and including deceased siblings).Whether the diabetic was an adopted child or ifthere are half-siblings or other adopted children inthe family should also be noted. If information on arelative is not known, it is coded as missing. It is alsohelpful if the name of the person who provided theinformation (the informant) and the source of data(i.e., mailed survey, interview, etc.) are recorded.

Similar data can also be collected for the child-ren of the diabetic index case (see box), the diabetic'sspouse, or extended family members. Forms for thistype of data collection may also need modificationfor use in more in-depth genetic or pedigree studies.

Identification numbers for family history data.Depending on the relationship (parents, sibs,spouses, children), the following identificationnumbers are recommended:

Relationship to IdentificationIDDM proband number

Parents:Natural 0101 = mother, 0102 = fatherStep 0201 = mother, 0202 = fatherAdopting 0131 = mother, 0132 = father

Sibs:Natural 0103 = oldest, then 0104, 0105, etc.

including IDDM proband in sibshipHalf 0203 = oldest, then 0204, 0205, etc.Adopted 0133 = oldest, then 0134, 0135, etc.

Spouses:For proband and 2101 = wife of 0103

natural siblings 2102 = husband of 01032201 = wife of 01042202 = husband of 0104, etc.

Children:For probands and 2103, etc. = natural children of 0103

natural siblings 2133, etc. = adopted children of 0103.

AcknowledgementsThis work was supported by National Institutes of HealthGrants R01 DK24021 and R01 DK39125.

ResumeEpidemlologle du dlab6te insulino-dependant(DID) familial: Standardlsation des donneespour le projet DIAMONDLe Projet multinational conduit par l'OMS pourl'etude du diabete juvenile et connu sous le nomde Projet DIAMOND est a l'origine de la creation

de registres du diabete insulino-dependant (DID),de la realisation d'etudes sur l'incidence dudiabete, de recherches en epid6miologie descrip-tive et d'investigations analytiques destinees atester les hypotheses sur l'etiologie de la maladie.Des donnees epid'emiologiques standardiseessont recueillies un peu partout dans le monde,autorisant des comparaisons internationales desdifferents registres. Des etudes multinationalesont commence a rechercher les determinantsgenetiques eventuels de la maladie et contribuentelles aussi au developpement mondial del'epidemiologie du diabete insulino-dependantfamilial.

L'epidemiologie du DID familial repose toutd'abord sur l'identification des cas de DID dans lesfamilies et sur l'evaluation du nombre de per-sonnes a risque pour la survenue de la maladiedans ces familles. Apres recueil des antecedentsfamiliaux de base pour un registre, il est possiblede determiner le risque de DID pour les membresdes familles habitant une region donnee et de lecomparer a l'incidence dans la population genera-le. L'etude descriptive d'agregats familiaux etl'investigation analytique de l'epidemiologie duDID chez les membres d'une famille peuvent ega-lement etre realisees. Grace au projet DIAMOND,le risque de DID chez les membres d'une mimefamille et le profil de l'agregation de la pathologiedans les families pourront etre compares d'ungroupe ethnique et d'un pays a l'autre. Une etudemultinationale des determinants eventuels del'incidence du DID familial sera en outre possible.L'exactitude des comparaisons internationales nepeut etre obtenue que si le recueil et I'analyse desdonnees de base sur les antec6dents familiauxsont standardises.

La codification du recueil des antecedentsfamiliaux de DID a une importance double: pourl1'tude multinationale des risques de recurrencedu DID dans les familles et pour I'analyse com-paree de certains determinants etiologiques duDID familial. Ces activites sont mises en oeuvredans le cadre du Projet DIAMOND.

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