The formation of the study populations for multiple imputation analysis, sensitivity analysis, and complete case analysis is presented.
eAppendix. Detailed description of the imputation process
eTable 1. Distributions of preclinical and clinical type 1 diabetes and background characteristics among children with complete and incomplete data on indoor dog/cat exposure during the first year of life
eTable 2. Association between microbial exposures during the first year of life and preclinical and clinical type 1 diabetes
Virtanen SM, Takkinen H, Nwaru BI, Kaila M, Ahonen S, Nevalainen J, Niinistö S, Siljander H, Simell O, Ilonen J, Hyöty H, Veijola R, Knip M. Microbial Exposure in Infancy and Subsequent Appearance of Type 1 Diabetes Mellitus–Associated AutoantibodiesA Cohort Study. JAMA Pediatr. 2014;168(8):755-763. doi:10.1001/jamapediatrics.2014.296
The role of microbial exposure during early life in the development of type 1 diabetes mellitus is unclear.
To investigate whether animal contact and other microbial exposures during infancy are associated with the development of preclinical and clinical type 1 diabetes.
Design, Setting, and Participants
A birth cohort of children with HLA antigen–DQB1–conferred susceptibility to type 1 diabetes was examined. Participants included 3143 consecutively born children at 2 hospitals in Finland between 1996 and 2004.
The following exposures during the first year of life were assessed: indoor and outdoor dogs and cats, farm animals, farming, visit to a stable, day care, and exposure to antibiotics during the first week of life.
Main Outcomes and Measures
Clinical and preclinical type 1 diabetes were used as outcomes. The latter was defined as repeated positivity for islet-cell antibodies plus for at least 1 of 3 other diabetes-associated autoantibodies analyzed and/or clinical type 1 diabetes. The autoantibodies were analyzed at 3- to 12-month intervals since the birth of the child.
Children exposed to an indoor dog, compared with otherwise similar children without an indoor dog exposure, had a reduced odds of developing preclinical type 1 diabetes (adjusted odds ratio [OR], 0.47; 95% CI, 0.28-0.80; P = .005) and clinical type 1 diabetes (adjusted OR, 0.40; 95% CI, 0.14-1.14; P = .08). All of the other microbial exposures studied were not associated with preclinical or clinical diabetes: the odds ratios ranged from 0.74 to 1.58.
Conclusions and Relevance
Among the 9 early microbial exposures studied, only the indoor dog exposure during the first year of life was inversely associated with the development of preclinical type 1 diabetes. This finding needs to be confirmed in other populations.
The hygiene hypothesis that microbial exposure during early life may affect susceptibility to the development of allergic diseases1 has been extended to investigate whether the hypothesis is true for autoimmune diseases, such as type 1 diabetes.2 Decreased environmental biodiversity through influence on human microbiota and its immunologic actions was recently implicated3 in the occurrence of atopic and other chronic inflammatory diseases.
Affluent and sparsely populated environments or less microbial diversity of the gut have been associated4 with the occurrence of type 1 diabetes. Increased maternal and child use of antibiotics was associated5 with an increased risk of type 1 diabetes in children. We set out to investigate whether contacts with animals or other microbial exposures during infancy are associated with the development of clinical or preclinical type 1 diabetes. Preclinical type 1 diabetes was defined as repeated positivity for both islet-cell antibodies and at least 1 of the 3 other autoantibodies analyzed and/or clinical type 1 diabetes.
We studied children belonging to the Oulu and Tampere cohorts of the Finnish Type 1 Diabetes Prediction and Prevention study. This multidisciplinary, population-based cohort study examines potential means to predict and prevent the manifestation of type 1 diabetes.6 Infants born with HLA antigen–conferred susceptibility to type 1 diabetes are monitored at 3- to 12-month intervals for diabetes-associated autoantibodies, growth, and environmental exposures until age 15 years or diagnosis of type 1 diabetes. The study procedures were approved by the local ethics committees and the parents provided written informed consent. Participants did not receive financial compensation.
The Finnish Type 1 Diabetes Prediction and Prevention Nutrition Study started in Oulu (Northern Botnia province, northern Finland) in 1996 and in Tampere (Pirkanmaa province, south-mid Finland) in 1997.7 Children born between September 2, 1996, and August 31, 2004, at Oulu University Hospital and between October 20, 1997, and September 5, 2004, at Tampere University Hospital were screened for HLA antigen–DQB1–conferred susceptibility to type 1 diabetes using cord blood samples.8 All deliveries in the area of these provinces took place in Oulu and Tampere university hospitals. Infants carrying increased genetic susceptibility (either high risk [HLA-DQB1*02 ⁄ 0302 heterozygous] or moderate risk [DQB1*0302 ⁄ x-positive; x indicates homozygosity or a neutral allele]) were invited to participate in the nutrition study (N = 7782). The nutrition study examines the relationship of maternal diet during pregnancy and lactation and the child’s diet during infancy and childhood with the development of type 1 diabetes, allergic diseases, and asthma in childhood. Of the children invited, 6078 participated in the assessment of type 1 diabetes end points. Of these, 4075 children who were participating in the dietary follow-up at age 5 years and had not received a diagnosis of clinical type 1 diabetes were invited to take part in the allergy study by completing a modified version of the International Study of Asthma and Allergies in Childhood questionnaire9 (named in the following allergy questionnaire) that included, in addition to asthma and allergy of the child and parents, questions on several microbial exposures during childhood. A total of 3143 children (77%) returned the allergy questionnaire. The flow diagram of the study participants is presented in the Figure.
The allergy questionnaire was completed by the parents when the child was aged 5 years. The following microbial exposures reported to have occurred during the first year of life were used in the analysis (all with yes/no response options): indoor/outdoor dog exposure, indoor/outdoor cat exposure, farm animal (cows, horses, sheep, goats, hens, other) exposure, farming occupation of the family, visit to a stable, and day care attendance. In Finland, dogs that are used for purposes such as hunting usually stay outside the house and may have little or no contact with children. The same is true for cats used to catch mice in a stable. Data on exposure to antibiotics during the first week of life (yes/no) were obtained from the medical birth registries of the 2 hospitals.
Information on the child's sex, maternal age, maternal professional educational level, and the number of siblings was recorded in a structured questionnaire completed by the parents after delivery. Information on the duration of gestation, mode of delivery, birth weight, and maternal smoking during pregnancy was retrieved from the medical birth registries of the 2 hospitals. Home municipality urbanization level was categorized according to Statistics Finland guidelines as rural, semiurban, and urban. Questions on parental history of asthma and allergic rhinitis and the child’s asthma, allergic rhinitis, and atopic eczema were also assessed in the allergy questionnaire. A child’s asthma was defined as physician-diagnosed asthma with either any wheezing symptoms or use of asthma medication during the preceding 12 months. Allergic rhinitis was defined as sneezing, nasal congestion, or rhinitis other than with respiratory infections, accompanied by itching of the eyes and tearing during the previous 12 months. Atopic eczema was defined as atopic eczema ever diagnosed by a physician.
Clinical and preclinical type 1 diabetes were used as outcomes. The latter was defined as repeated positivity for islet-cell antibodies plus for at least 1 of 3 other diabetes-associated autoantibodies and/or clinical type 1 diabetes. The definition used for preclinical type 1 diabetes is closely related to clinical disease: approximately 60% to 70% of children with preclinical diabetes are expected to progress to the clinical disease within the next 8 years.10 When a child seroconverted to positivity for islet-cell antibodies for the first time, all of the child’s preceding (starting from birth) and subsequent serum samples were analyzed for insulin autoantibodies, autoantibodies to glutamic acid decarboxylase, and insulinoma-associated 2 molecule. Islet-cell antibodies were detected by a standard indirect immunofluorescence method. Insulin autoantibodies were quantified with a microassay and glutamic acid decarboxylase and insulinoma-associated 2 molecule autoantibodies with specific radiobinding assays.11 Maternal autoantibodies transferred through the placenta were excluded from the analyses. In the present study we used follow-up for type 1 diabetes–associated autoantibodies and type 1 diabetes up to January 1, 2013. Follow-up for clinical diabetes was available for all children who started the study (n = 6078) until January 2013.
For a sensitivity analysis data series we used 2740 participant records, which were based on prospective interviews conducted by study nurses at the 12-month visit and were available only for children observed at Tampere University Hospital. Study nurses recorded on an open-ended table whether the family had indoor animals and, if so, which animals during the first year of the child’s life. Indoor animals other than dogs and cats were infrequent and were not included. The other microbial exposures were not available from the sensitivity analysis data series.
Logistic regression was used to estimate the associations between microbial exposure and preclinical and clinical type 1 diabetes. The possible dependence among siblings was accounted for by using the generalized estimating equations with the sandwich estimator of variance to estimate regression coefficients in logistic regression analyses.12 Potential confounders adjusted in the models were sex, genetic risk according to HLA-DQB1 (moderate/high), family history of diabetes mellitus (yes/no), mode of delivery (vaginal/cesarean section), place of birth (Tampere/Oulu), parental asthma or allergic rhinitis (yes/no), maternal professional educational level (none, professional education/course, secondary professional education, university), maternal age (<25, 25-29, 30-34, and ≥35 years), home municipality urbanization level (rural, semiurban, urban), and the presence of asthma (yes/no) and atopic eczema (yes/no) in the child by the age of 5 years. The confounders were chosen based on earlier findings from the literature13 (eg, mode of delivery) or/and being associated with (P < .20) both the exposure and the end point in the present study. Analyses were performed for all observed exposure data (complete case analysis), for exposure data obtained from Tampere University Hospital medical records (sensitivity analysis), and on multiply imputed data (Supplement [eAppendix]). Multiple imputation was performed to correct for potential biases associated with missing values in explanatory variables.14 There was a considerable chance for bias for 2 reasons: (1) the exposure variables were not obtained for the type 1 diabetes cases that were diagnosed before the allergy questionnaire assessment and, according to the study design, were ineligible for further follow-up; and (2) other dropouts by the age of 5 years. Only 3143 of the 6078 children (51.7%) for whom type 1 diabetes end point information was available had returned the allergy questionnaire, resulting in a high proportion of missing values on the microbial exposures. To make multiple imputations for these variables as effective as possible, surrogate data from Tampere University Hospital medical records were used in the imputation models. Because information on only indoor dog and cat exposure was obtained from the medical records, multiple imputation was done only for those 2 microbial exposures. All other variables involved in the imputation model were also imputed themselves. A detailed description of the imputation process is presented in the Supplement (eAppendix). The κ coefficients for the agreement between indoor dog and cat exposure during the first year of life obtained from the allergy questionnaire and participants’ medical records were calculated. Analyses were performed using SAS, version 9.2 (SAS Institute Inc).
Table 1 reports the baseline characteristics and allergic diseases of the participating children according to indoor dog and cat exposure in the complete case data. Preclinical type 1 diabetes was present in 5.5% of the children (173 of 3143) and clinical type 1 diabetes was present in 1.6% of the children (51 of 3143) in the complete case data set. The preclinical outcome was based on clinical diabetes in 2 children. The median (range) time of manifestation of preclinical type 1 diabetes was 5.0 (1.0-13.2) years, and that of clinical type 1 diabetes was 9.2 (5.3-14.7) years. The median (range) length of follow-up was 10.0 (1.0-15.3) years for preclinical and 12.2 (5.3-16.3) for clinical type 1 diabetes. The frequency of preclinical and clinical type 1 diabetes was higher among boys, children carrying high- compared with moderate-risk HLA genotype, those with a family history of type 1 diabetes, and children whose mothers had not received professional education. Clinical type 1 diabetes was more common among children of older mothers. Preclinical type 1 diabetes was more prevalent among children with than without asthma, whereas the opposite was true for atopic eczema (data not shown).
The farming occupation of the family, visit to a stable, and day care attendance during the first year of life, as well as the use of antibiotics during the first week of life, were not significantly associated with the outcomes, with adjusted odds ratios (ORs) for preclinical type 1 diabetes varying from 1.15 to 1.56 and for clinical type 1 diabetes from 0.74 to 1.58 (Table 2). Of the indoor and outdoor dog and cat and farm animal contacts during the first year of life, only indoor dog exposure was inversely associated with the development of preclinical type 1 diabetes in the complete case analysis (adjusted OR, 0.47; 95% CI, 0.28-0.80; P = .005) (Table 2). Indoor dog exposure had an OR of 0.40 (95% CI, 0.14-1.14; P = .08) for clinical type 1 diabetes. The OR for outdoor dog exposure was 1.14 for preclinical and 1.15 for clinical disease; for other animal exposures, ORs varied from 0.93 to 1.02 and from 0.79 to 1.34, respectively (Table 2).
In the sensitivity analysis series of 2740 children from Tampere University Hospital, preclinical type 1 diabetes was present in 6.2% (169) and clinical type 1 diabetes was present in 3.0% (82) of the children. The median (range) time of manifestation was 4.0 (0.8-13.2) years for preclinical type 1 diabetes and 5.7 (1.1-13.2) years for clinical type 1 diabetes. The median (range) length of follow-up was 8.1 (0.2-14.5) years for preclinical and 11.7 (1.1-15.2) for clinical type 1 diabetes.
We obtained data on indoor dog and cat exposure during the first year of life from both the allergy questionnaire (complete case data) and from Tampere patient records (sensitivity analysis data) for 1843 children. Of these, 19.9% (367) were exposed to a dog according to the allergy questionnaire and 18.5% (341) were exposed according to patient records; 47 children were exposed to a dog according to only the allergy questionnaire and 21 according only to patient records. The κ coefficient for the agreement between the methods was 0.88. The κ coefficient for the agreement of cat exposure was 0.82.
The sensitivity analysis showed similar ORs compared with complete cases analysis for the association between indoor dog exposure and preclinical type 1 diabetes (OR 0.58; 95% CI, 0.31-1.09; P = .09) and clinical type 1 diabetes (OR, 0.17; 95% CI, 0.02-1.31; P = .09) (Table 3). The proportions of disease outcomes by cat exposure were similar (Table 3) according to both types of analysis.
Distributions of preclinical and clinical type 1 diabetes and background characteristics among children with complete and incomplete data on indoor dog and cat exposure during the first year of life are presented in the Supplement (eTable 1). After adjustment for potential confounding variables, indoor dog exposure was inversely associated with the development of preclinical type 1 diabetes in the multiple imputation data analysis (OR, 0.54; 95% CI, 0.34-0.88; P = .01), but not significantly associated with clinical type 1 diabetes (Supplement [eTable 2]). Indoor cat exposure was not significantly associated with the development of preclinical or clinical type 1 diabetes (Supplement [eTable 2]).
In the present study, several farming- and animal contact–related factors, day care attendance, and antibiotic use during early infancy were studied. Of these factors, only indoor dog exposure was inversely associated with subsequent development of preclinical type 1 diabetes. This association was consistently seen in both complete case and multiple imputation data analyses. Outdoor dog exposure showed a nonsignificant OR (1.14) with preclinical diabetes outcome.
The birth cohort of children with increased genetic susceptibility to type 1 diabetes was closely observed at 3- to 12-month intervals with frequent measurements of the type 1 diabetes end points. The participation and retention rates of the study were good. Although the number of children with clinical type 1 diabetes was relatively small, the number of preclinical end points was moderate.
The questions about animal contacts, farming, and day care were retrospectively asked with detailed and validated questions when the child was aged 5 years. We could show in a subpopulation that the reliability of the indoor dog and cat contact data collected at that time was good in comparison with the data collected from patient records when the child was aged 12 months. Participation in our study ended if the child received a diagnosis of type 1 diabetes. Consequently, our complete case data source for animal and other microbial data collected at age 5 years did not include children who developed diabetes at a younger age. To decrease the probability of outcome-dependent bias we conducted the analysis in 2 further data sets: evaluating patient records (sensitivity analysis) available for 1 of the clinics and undertaking multiple imputation for the whole cohort, using partially observed data. Both data sets included children with a diagnosis of type 1 diabetes when they were younger than 5 years (Figure). In the sensitivity analysis data, the ORs for indoor dog and cat exposure were similar to those of complete case analysis and multiple imputation analysis. In sensitivity analysis, we found no indication that the risk associated with dog or cat exposure would have been different among children younger than 5 years compared with older children.
The numbers of children with outdoor and farm animal exposure, farming occupation of the family, or early use of antibiotics were low and CIs were wide, making the estimates uncertain. However, the only statistically significant finding in the present study, the inverse association between indoor dog exposure and preclinical type 1 diabetes, can be a spurious finding. We used multiple imputation to try to address the problem of dropouts from the initial 6078 children to 3143 at the 5-year follow-up. Multiple imputation relies on an assumption that data are missing at random, that is, the probability of missingness is independent of the unobserved data, given the observed characteristics. We included several characteristics in the imputation model (Supplement [eTable 1]), but we may have missed some important factors associated with the missingness mechanism. Although we cannot rule out the possibility that the data are not missing at random, in the sense of standard multiple imputation terminology, we believe that the similarity of the results of the multiple imputation and complete case analyses suggest that the missingness is not a source of significant bias. In the sensitivity analysis the proportion of missing data was, however, smaller than in the complete case data (Figure). The limitations of the study also include a possibility of selection bias, because 22% of the invited families declined to participate.
In a Swedish cohort study,15 the presence of a cat or dog at home or day care during the first year of life was directly associated with positivity for glutamic acid decarboxylase (crude OR, 1.3) and cat exposure with positivity for insulinoma-associated 2 molecule (crude OR, 1.4), but neither of these exposures was related to simultaneous positivity of the 2 autoantibodies. A hospital-based German case-control study16 did not find evidence that regular contact with a stable (adjusted OR, 1.2; 95% CI, 0.5-2.7) or any specific farm animal or pet was associated with type 1 diabetes. The adjusted ORs (95% CI) for regular dog and cat contacts were 0.67 (0.44-1.04) and 0.86 (0.55-1.35), respectively, in that study. The ORs for contact with a stable and dogs were relatively close to our results.
Indicators of social mixing and crowding, such as day care attendance, having siblings, sharing bedrooms, and regular changes in place of residence, have been associated17- 19 with a decreased risk of type 1 diabetes in case-control studies. In cohort studies,20,21 including the present study, attendance at a day care facility was not associated with preclinical or clinical type 1 diabetes. In children aged 3 years and younger, the area per person was directly related to type 1 diabetes in an Italian study.21 The rising incidence of type 1 diabetes in children in several affluent countries has been linked22,23 to increasing standards of living and socioeconomic transformation.
Children susceptible to type 1 diabetes may have less bacterial diversity and less stable microbiota.24 Enterovirus infections, especially toward coxsackievirus B, may play a role in the cause of type 1 diabetes.25,26 There is evidence that the enterovirus load in the gut is larger among individuals with type 1 diabetes than in those without diabetes.26
A case-control study5 nested in a population-based cohort linked frequent early antimicrobial use to the development of type 1 diabetes: more than 7 purchases resulted in an OR of 1.7. In the present study, we had information only on the use of antimicrobials during the first week of life and found no indication of any association with type 1 diabetes.
Dog contact may affect the human immune system in many ways. Dog contact has been shown27 to protect children from respiratory infections during the first year of life, and cat and/or dog ownership may reduce the risk of gastroenteritis.28 Dogs may also induce alterations in home microbial communities and spread infections including helminthes, thus affecting immune regulation.29 In addition to affecting adaptive immune responses,30,31 early exposure to dogs may reduce innate immunity responses.32
Most of the microbial factors evaluated in the present study were not associated with preclinical or clinical type 1 diabetes. Early exposure to an indoor dog may protect a child from preclinical type 1 diabetes. This observation needs to be confirmed in additional studies.
Accepted for Publication: February 5, 2014.
Corresponding author: Suvi M. Virtanen, MD, PhD, Nutrition Unit, National Institute for Health and Welfare, PO Box 30, FI-00271 Helsinki, Finland (email@example.com).
Published Online: June 23, 2014. doi:10.1001/jamapediatrics.2014.296.
Author Contributions: Drs Virtanen and Takkinen had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Virtanen, Takkinen, Nwaru, Kaila, Nevalainen, Simell, Hyöty, Veijola, Knip.
Acquisition, analysis, or interpretation of data: Virtanen, Takkinen, Nwaru, Kaila, Ahonen, Nevalainen, Niinistö, Siljander, Simell, Hyöty, Veijola, Knip.
Drafting of the manuscript: Virtanen, Takkinen, Nwaru, Nevalainen.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Takkinen, Nwaru, Nevalainen.
Obtained funding: Virtanen, Simell, Hyöty, Veijola, Knip.
Administrative, technical, or material support: Virtanen, Kaila, Ahonen, Siljander, Simell, Ilonen, Veijola, Knip.
Study supervision: Virtanen, Nevalainen, Veijola, Knip.
Conflict of Interest Disclosures: None reported.
Funding/Support: The study was supported by the Academy of Finland (grants 44105, 48724, 80846, 201988, 126813, and 129492, and Centre of Excellence in Molecular Systems Immunology and Physiology Research 2012-17 grant 250114); the Prevaller Consortium; the European Foundation for the Study of Diabetes (EFSD/Novo Nordisk Partnership and ESFD/Juvenile Diabetes Research Foundation/Novo Nordisk Programme); the Foundation for Pediatric Research; the Tampere Tuberculosis Foundation; the Juho Vainio Foundation; the Yrjö Jahnsson Foundation; Medical Research Funds, Turku University Hospital and Oulu University Hospital; the Juvenile Diabetes Research Foundation; Novo Nordisk Foundation; EU Biomed 2 Program (grant BMH4-CT98-3314); and the Competitive Research Funding of the Tampere University Hospital (grants 9B099, 9C084, 9D081, 9E082, 9F089, 9G087, 9H092, 9J147, 9K149, 9L117, 9M114, 9N086, and 9P057).
Role of the Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: We thank the physicians, research nurses, nutritionists, and laboratory staff of the Type 1 Diabetes Prediction and Prevention Study for their continuous collaboration through the years. We express our gratitude to Eeva Korhonen (Tampere University Hospital), Sirpa Pohjola (Oulu University Hospital), and Katri Jokinen, MSc (University of Tampere), for their expert technical assistance. The contributors did not receive financial compensation.