Carsten Obel

Jørn Olsen

Tine Brink Henriksen

Alina Rodriguez

Marjo- Riitta Järvelin

Irma Moilanen

Erik Parner

Karen Markussen Linnet

Anja Taanila

Hanna Ebeling

Einar Heiervang

Mika Gissler

Marjo- Riitta Järvelin

Tine Brink Henriksen

Marjo-Riitta Järvelin

Is maternal smoking during pregnancy a risk factor for Hyperkinetic disorder? -Findings from a sibling design

Keywords: smoking, pregnancy, Attention Deficit Hyperactivity Disorder, sibling design, Hyperkinetic Disorder smoking, pregnancy, Attention Deficit Hyperactivity Disorder, Hyperkinetic Disorder, sibling design

Background Studies have consistently shown that pregnancy smoking is associated with twice the risk of hyperactivity/inattention problems in the offspring. An association of this magnitude may make behavioural difficulties one of the most important health effects related to smoking during pregnancy. However, social and genetic confounders may fully or partially account for these findings.

Methods A cohort including all singletons born in Finland January 1, 1987 through December 31, 2001 was followed until January 1, 2006 based on linkage of national registers. Data were available for 97% (N=868 449) of the population. We followed singleton children of smoking and non-smoking mothers until they had an ICD-10 diagnosis of Hyperkinetic disorder (HKD) or to the end of the observation period. We used sibling-matched Cox regression analyses to control for social and genetic confounding.

Results

We found a much smaller association between exposure to maternal smoking during pregnancy and risk of HKD in children using the sibling-matched analysis (HR=1.20, 95% CI 0.97-1.49) than was observed in the entire cohort (HR 2.01, 95% CI: 1.90-2.12).

Conclusions Our findings suggest that the strong association found in previous studies may be due to time stable familial factors, such as environmental and genetic factors. If smoking is a causal factor, the effect is small and less important than previous studies indicate.

Background

Attention Deficit Hyperactivity Disorder (ADHD) defined by the DSM-IV criteria is one of the most common childhood psychiatric disorders 1 , with a cumulative incidence of 2-5% 2 . In the WHO diagnostic classification system (ICD-10) used in Europe, only children with the most severe ADHD combined type (both inattention and hyperactivity/impulsivity symptoms) receive a diagnosis of Hyperkinetic Disorder (HKD) 3 . Core symptoms are linked to poor school performance and other social problems 4 .

HKD has at least in part genetic causes 5 and brain imaging studies suggest that deviant brain morphology may be present at birth, which indicates a genetic etiology or aetiology related to prenatal environmental exposure 6 . A number of pregnancy exposures have been suggested with smoking as a strong candidate 7;8 . An association between prenatal exposure of the brain to nicotine and attention problems in the offspring seems biologically plausible. A number of animal studies, including studies on monkeys, with endpoints that mimic the disorder, suggest that prenatal exposure to nicotine may influence fetal brain development in a way that is compatible with ADHD 9 . Epidemiological studies have consistently shown that mothers who smoke during pregnancy have about twice the risk of HKD 10 and ADHD 11 in their offspring and an association of this magnitude may make behavioural difficulties one of the most important health effect related to smoking during pregnancy.

However, both smoking and HKD correlate with social conditions and women with attention problems may be likely to be smokers 12 . Nicotine improves attention 13 and smoking may simply be an indicator of a genetic disposition to HKD. It has therefore been suggested that the association between prenatal smoking and offspring ADHD could be due to genetic and social confounding rather than the smoking exposure per se 14 . Ruling out this possibility in conventional observational designs is not easy and alternatives are called for A recent study of in vitro fertilised pregnancies examined children conceived through genetically unrelated egg-donations and found no evidence of an effect of smoking 15 . Two other recent studies found only weak associations when using a sib-ship design 16 17 . Both studies raise doubt about the causality of the association, but all were based on proxy measures of the disorder and had serious limitations.

The sibling design may provide one of the most efficient approaches to control for family factors when large epidemiological cohorts and sufficient discordant siblings are available 18 . In this study we followed the entire population of children born in Finland during a 15year period and estimated the association between prenatal smoking and the ICD-10 diagnosis of HKD in sibling pairs discordant for prenatal exposure to smoking and HKD.

Materials and methods

Setting

Finland has a mandatory registration of all births in the Finnish Medical Birth Register (FMBR). By using the unique personal identification number covering all residents in Finland, we linked all births from 1987 to 2001 with data from the Finnish Hospital Discharge Register (FHDR) including all inpatient (established in 1967) and all outpatient visits (established in 1998). Registration is mandatory for all inpatient care in public and private hospitals as well as for all outpatient visits in public hospitals. All diagnoses were reported using ICD-9 up to 1996 where ICD-10 was used 19 . We identified all singleton children born from January 1, 1987 to December 31, 2001 who were still alive on January 1 st , 2006 yielding a total of 894,697 singletons.

The National Institute for Health and Welfare (THL), which is the body responsible for the Finnish Medical Birth Register and Finnish Hospital Discharge Register, gave permission to link and use encrypted health register data for this study. The data protection ombudsman was informed about the study, as requested by the national data protection regulation.

Exposure information

Antenatal care in Finland is tax-paid and offered to all pregnant women and the care in low risk pregnancy includes approximately 10-14 antenatal visits. The data on maternal smoking stemmed from concurrent information provided by pregnant women and systematically collected by midwives and public health nurses, during the second trimester of routine antenatal care and subsequently archived in the FMBR. During the period from 1987 to 1990, responses were categorised either as non-smokers, smokers of less than 10 cigarettes per day, or 10 cigarettes or more per day. During the period 1991 to 2001 the average number of cigarettes per day was not collected, but replaced with information on whether or not women stopped smoking during first trimester. In the sibling-matched analyses we defined pregnancy smoking as smoker and non-smoker, and for mothers of children born 1991-2001 only those who reported continuing smoking as well as those only smoking during the first trimester were categorised as smokers.

Outcome definition

We studied the children's entries in the FHDR until January 1 st , 2006 using ICD-10 diagnoses to identify children with HKD including hyperkinetic disorder (F90.0), hyperkinetic conduct disorder (F90.1) or other hyperkinetic disorder (F90.8 and F90.9) as endpoints in the analyses. We excluded 1901 children with pervasive developmental disorders, including autism, F84 (N=1095), mental retardation, F70-79, (N=262) and 325 with both these diagnoses. Further 219 children who had the ICD-9 (but not the ICD-10) diagnosis of 314 were excluded from the analyses, because the definition was not fully comparable with ICD-10.

Cohort definition

After the above were excluded, the population included 892,796 children of whom 7,226 were diagnosed with HKD. There were 24,347 (3%) with missing smoking information, leaving 868,449 available for analyses, where 7023 children (0.8%) had HKD. Among the 443,076 boys, there were 6013 (1.4 %) and among the 425,353 girls there were 1010 (0.2%) that received the HKD diagnosis during the observation period. The 513,198 participating women contributed with an average of 1.7 children to the entire cohort.

Statistical analyses

To control for differences in length of follow up time we used the Cox regression analysis, with child age as the primary time scale. To control for the increasing incidence of HKD over study time, we adjusted for each year of birth as a categorical variable (1987-2001).

F o r R e v i e w O n l y
We further a priori decided to adjust for child sex, gestational age at birth (less than 30, 30-33, 34-36,37-40,41 or more), maternal age (20 or less, 21-25, 26-30,31-35, 36 or more) and parity (0,1,2,3 or more). Data on maternal occupation was available and adjusted for in the period 1991 to 2001 and was transformed to an indicator of socioeconomic status (SES) according to a national system of classifications and standards in Finland 20 (upper white collar, lower white collar, blue collar, others). The analyses were performed using STATA 9.0. Hazard Ratios (HR) and are presented with 95% confidence intervals (CI).

Our analytic strategy was to analyze the entire population using regular cohort analyses and then to compare these findings with sibling-matched analyses.

Population cohort analyses

In the Cox regression model, we assumed proportional rates for the exposure and the above-mentioned potential confounders with one common baseline rate function. The proportional hazards assumption was evaluated for all variables by comparing estimated log-minus-log survivor curves over the different categories of variables investigated. Because most women contributed to the cohort with more than one child, we used robust standard errors to adjust the confidence intervals for the presence of siblings in the population analyses (declaring each of the sibling pairs to be a cluster). All analyses were repeated by sex and adjusted for the variables described above. Additionally, in order to control for SES and because of changes in exposure registration, we separated the cohort into children born 1987-1990 and 1991-2001, where SES was available for the latter group.

Sibling-matched analyses

We performed sibling-matched analyses to control for shared genetic and social confounding. We used stratified Cox regression with a separate stratum for each family identified by the mothers encrypted identification number. In the stratified Cox regression model, each family has its own baseline rate function reflecting the family's shared genetic and social factors. The exposure comparisons, smoking versus non-smoking, are thus made within the family. We controlled for the same factors as in the cohort analyses, except for SES, which is part of the shared social factors and therefore already controlled for in the sibling-matched analysis. The stratified Cox regression model is an extension of the paired binomial model, taking into account the differences in follow-up time. Thus only sibling pairs discordant for smoking as well HKD were 'informative', i.e. contributed information to the estimates. Indeed, to be informative, the sibling without HKD should have at least as long a follow-up time as the sibling with HKD.

Results

In the regular cohort analyses we found that children exposed to maternal smoking in pregnancy had about twice the risk of receiving a diagnosis of HKD during up to 19 years follow-up period (HR 2.01, 95% CI: 1.90-2.12). The results of the analyses in the two periods are shown in table 1. The analyses of children born 1987-1990 indicated that HKD risk increased by level of smoking. In a similar way, the data for children born 1991-2001 suggested that those who quit smoking in early pregnancy had a slightly lower risk for HKD as compared with those who continued smoking beyond the first trimester, but this difference was not statistically significant. Excluding children born small for gestational age or preterm did not change the results. Control for SES among children born 1991-2001

F o r R e v i e w O n l y
only slightly changed the estimates and the results were very similar in the two time periods.

(TABLE 1 about here)

The results comparing smokers with non-smokers in the full cohort and in the siblingmatched analyses are shown in Table 2. The adjusted analyses suggested a weak association between antenatal smoking exposure and HKD when boys and girls were analysed together and separately.

We finally analysed possible birth order effects by stratifying the analyses by whether the smoking exposure was in the pregnancy of the older or the younger sibling and then whether the HKD diagnosis was given to the older or the younger sibling. The associations were similar for women smoking in the pregnancy of the older and the younger child (HR=1.3 and 1.2 respectively)

(TABLE 2 about here)

Discussion

During a 15 year observation period of the entire Finnish population, we found in the cohort analysis that children prenatally exposed to maternal smoking had twice the risk of being diagnosed with HKD than children of non-smokers. This finding is in line with recent studies, 21;22 a number of previous conventional case control and cohort studies that have reported a strong association between pregnancy smoking and various measures of the ADHD phenotype, 11 as well as the diagnosis of HKD 10 . However, in the sibling-matched analyses, when controlling for shared family confounders, the estimated association was much weaker. This finding indicates that a part of the association reported in most previous studies may be partly due to confounding as maternal smoking may be indicator of a genetic trait and social factors related to HKD. These findings are in line with the findings of three recent studies.Thapar et al. used children born after different types of in vitro fertilisation with egg-donation as a way to distinguish between genetic and exposure effects 15 . They found no association between smoking and the ADHD phenotype in genetically unrelated mother-child pairs, which however could be due to chance by small sample size or that they had more girls among the offspring of exposed 23 . Two recent studies used the sibling design with endpoints of relevance for ADHD. D'Onofrio et al. studied the association between pregnancy smoking and hyperactivity problems based on parents answering three screening questions and found a considerably smaller effect using the sibling design as compared to the regular cohort analyses 16 . The same tendency was seen in a register-based Swedish study that studied the association between smoking in pregnancy in all Swedish children born 1987-2000 and prescriptions of ADHD medication in the year 2006 17 . In their sibling analyses, they reported an estimate quite close to ours, but the crude proxy for ADHD, a one-year registration of prescriptions, did not capture older siblings treated medically early on in life. This is quite important in the sibling design because discordant sibling pairs are misclassified as concordant and vice versa. The present study has a number of strengths. It is based on a complete 15 year follow-up using established diagnostic criteria of clinical examinations from specialised departments within the public health service. We had almost complete follow-up data with little risk of selection bias, our data came from concurrently registered information rather than retrospective reports. Finally our results were unlikely to be flawed by differential misclassification of HKD because children's care is universally available, publicly financed and organised in Finland. It is unlikely that the threshold for admission to hospital clinics is related to the prenatal smoking, especially when siblings are compared.

The matched-sibling design has a number of advantages in controlling for family factors. These family factors are difficult to measure and control for in conventional cohort designs. Full siblings share social environment, but only 50% of their genes, so even these analyses will tend to overestimate the tested association. One caveat of our study is that siblings were matched on the mother's identification number and we did not have any information regarding fathers (due to strict data protection regulations in Finland). It may be that our estimates overestimate the association and that even weaker associations would have been found if we were able to identify and exclude half-siblings.

There are limitations to the sibling design that should be mentioned. The strict control for shared family factors limits the analyses to a small subset of the population. Only sibling pairs discordant for smoking as well as HKD contribute to the estimate in these analyses.

In the present study, we had 40,615 sibling pairs, that were discordant for prenatal smoking exposure, but because discordance for HKD was also needed for a pair to be informative, only 880 pairs contributed with information of the smoking-HKD association. In the adjusted stratified Cox regression model, more sibling pairs discordant for some of the other factors in the model will primarily add to the estimates, but the basic concept of this type of analyses can simply be illustrated by the ratio between the informative pairs supporting and discounting the hypothesis.

Positive association pairs (PAP) are sibling pairs that support a positive association between smoking and HKD i.e. where the mother smoked during the pregnancy of the child with HKD and did not smoke in the pregnancy with the child without HKD. Negative association pairs (NAP) on the other hand were pairs where the mother did not smoke in the pregnancy of the child with HKD and smoked in the pregnancy of the child without HKD. To support the idea that prenatal smoking is a causal factor for HKD, one would expect more PAP than NAP, in fact twice as many to support the findings of most previous studies. Of the 880 pairs, 484 pairs were PAP and 396 NAP with a ratio (1.2) very close to the results of the crude Cox regression analyses shown in Table 2. When restricted to comparison between boy siblings, the PAP/NAP ratio was 1.3 (218/168) and restriction to girl siblings resulted in a ratio of 1.8 (45/25). Again the ratios are in line with the estimates for sibling-matched Cox regression analysis and the small numbers explain the broad confidence intervals.

As illustrated above, large register-based studies are needed to gain valid estimates from sibling analyses. In this type of register, the information on smoking is collected routinely, but the smoking information is quite crude. The crude smoking information limits our ability to estimate effect of timing and dose. There are, however, further potential limitations to the interpretations of our results linked to the strict selection of smoking women in the sibling analyses. As mentioned above, the sibling-matched analyses are based on a subsample of smoking women and this sample may differ from the smoking women who were not informative in the sibling analyses. We therefore compared women reporting smoking and giving birth to their first child 1987-1991 according to whether they smoked in their next pregnancy. Among those who smoked in both pregnancies, 85% (95% CI: 84-86%) were smoking 10 cigarettes or more in the pregnancy of the first child as compared with 71% (95% CI: 70-72%) of subsequent non-smokers This indicates that there are more heavy smoking women among those who were unable to give up smoking in any of their pregnancies. Thus heavy smoking women are underrepresented in the sibling analysis and this may be part of the explanation for the attenuated estimates as compared with the regular cohort analyses.

It could further be argued that because information on smoking was based on personal contact between midwives/public health nurses and the pregnant women, the difference in unmatched and matched results could be due to misclassification of smoking status. Some misclassification seems likely and may be part of the explanation for the attenuation in our estimates when using sibling analyses. Women who contributed to the sibling analyses with informative siblings were characterised by having smoked in one pregnancy and by having a child with HKD. It is possible that women with HKD in the family may be more likely to under-report smoking. If this bias is non-differential, which is expected, it would bias toward null-values and could partly explain the attenuation of the association. We were not able to evaluate this possibility directly, because we did not have access to detailed smoking information, but we may evaluate this potential misclassification by looking at differences in birth weight between siblings with discordant smoking exposure. The effect of antenatal smoking on birth weight is well established and if women contributing to our informative pairs more often under-reported true smoking in the subsequent pregnancy, we would expect a smaller difference in birth weight between these sibling pairs compared with all sibling pairs discordant for smoking exposure. This was however not the case. We found no difference in the effect of smoking on birth weight. In the informative pairs adjusted for parity, gestational age at birth and gender, there was a reduction of 88 grams (95% CI: 53-123 grams) in birth weight as compared with 69 grams (95% CI: 63-75 grams) in all the sibling pairs discordant for smoking. These differences in birth weight are in line with results from a recent report, where smoking information was validated against serum cotinine 24 . These findings contest the possibility that the attenuation of the association was due to more misclassification of smoking status in the informative sibling pairs. By using a HKD diagnosis as the endpoint, we had the possibility to study the more severe phenotype. A HKD diagnosis requires hyperactivity/impulsivity as well as inattention in at least two settings and is close to the DSM-IV ADHD-combined diagnosis. Although the Finnish register contains complete information for in-as well as outpatient contacts in the public health system, some children are unrecognized and thus untreated or treated without contact to the hospital system. Accordingly, some cases of HKD or ADHD are undiagnosed in the hospital system, but as they are few in the general population it will have little influence on the estimation of the association in our study. Even a low sensitivity will not bias our results as long as the specificity is high, which we find likely due to the use of strict diagnostic criteria in clinical practice in Finland. Differences in referral, which in conventional studies may lead to bias, are less likely to do so in a sibling design because

F o r R e v i e w O n l y
this bias is likely to be linked to the families. However, it is also possible that a diagnosis given to a child will make it more likely that an undiagnosed sibling with the disorder will be diagnosed. In the sibling design this would generate less discordant pairs, but if linked to smoking attenuate the estimate.

In conclusion, previous reports may have overestimated the association between pregnancy smoking and HKD because they have not been able to control for shared family factors. We cannot completely discount the possibility that smoking is a causal factor, but then the size of the effect is probably smaller than what previously has been reported. Our findings are based on women, who were able to change smoking status between pregnancies and these results most probably cannot be extrapolated to women who smoked in all their pregnancies. From a public health perspective, however, it is of interest to estimate whether women, who manage to quit smoking during a pregnancy actually reduce their risk of having a child with behaviour problems. This study indicates that this may be the situation for very few.

Funding

Abstract

Background Studies have consistently shown that pregnancy smoking is associated with twice the risk of hyperactivity/inattention problems in the offspring. An association of this magnitude may make behavioral difficulties one of the most important health effect related to smoking during pregnancy. However, social and genetic confounders may fully or partially account for these findings.

Methods A cohort including all singletons born in Finland January 1, 1987 through December 31, 2001 was followed until January 1, 2006 based on linkage of national registers. Data were available for 97% (N=868 449) of the population. We followed singleton children of smoking and non-smoking mothers until they had an ICD-10 diagnosis of Hyperkinetic disorder (HKD) or to the end of the observation period. We used sibling matched Cox regressions analyses to control for social and genetic confounding.

Results

We found a much smaller association between exposure to maternal smoking during pregnancy and risk for HKD in children using the sibling matched analysis (HR=1.20, 95% CI 0.97-1.49) than seen in the entire cohort (HR 2.01, 95% CI: 1.90-2.12).

Conclusions

Background

Attention Deficit Hyperactivity Disorder (ADHD) defined by the DSM-IV criteria is one of the most common childhood psychiatric disorders 1 , with a cumulative incidence of 2-5% 2 .

In the WHO diagnostic system (ICD-10) used in Europe only children with the most severe ADHD combined type (both inattention and hyperactivity/impulsivity symptoms) receive a diagnosis of Hyperkinetic Disorder (HKD) 3 . Core symptoms are linked to poor school performance and other social problems 4 .

HKD has at least in part genetic causes 5 and brain imaging studies suggest that deviant brain morphology may be present at birth which indicate a genetic etiology or etiology related to prenatal environmental exposure 6 . A number of pregnancy exposures have been suggested with smoking as a strong candidate 7;8 . An association between prenatal exposure of the brain to nicotine and attention problems in the offspring seems biologically plausible. A number of animal studies, including studies on monkeys, with endpoints that mimic the disorder, suggest that prenatal exposure to nicotine may influence fetal brain development in a way that is compatible with ADHD 9 . Epidemiological studies have consistently shown that mothers who smoke during pregnancy have about twice the risk of HKD 10 and ADHD 11 in their offspring and an association of this magnitude may make behavioral difficulties one of the most important health effect related to smoking during pregnancy.

However, both smoking and HKD correlate with social conditions and women with attention problems may be likely to be smokers 12 . Nicotine improves attention 13 and smoking may simply be an indicator of a genetic disposition to HKD. It has there for been suggested that the association between prenatal smoking and offspring ADHD could be due to genetic and social confounding rather than the smoking exposure per se 14 . To rule out this possibility out in conventional observational designs is not easy and call for alternative designs. A recent study of in vitro fertilized pregnancies examined children conceived by egg-donation who are genetically unrelated to their mothers and found no evidence of an effect of smoking 15 . Two other recent studies found only weak associations when using a sib-ship design 16 17 . These studies together raise doubt about causality of the association. However, all were based on proxy measures of the disorder and had serious limitations.

The sibling design may provide one of the most efficient approaches to control for family factors within when large epidemiological cohorts are available when sufficient discordant siblings are available 18 . In this study we followed the entire population of children born in Finland during a 15-year period and estimated the association between prenatal smoking and the ICD-10 diagnosis of HKD in sibling pairs discordant for prenatal exposure to smoking and HKD.

Materials and methods

Setting

Finland has a mandatory registration of all births in the Finnish Medical Birth Register (FMBR). By using the unique personal identification number covering all residents in Finland, we linked all births from 1987 to 2001 with data from the Finnish Hospital Discharge Register (FHDR) including all inpatient (established in 1967) and all outpatient visits (established in 1998). Registration is mandatory for all inpatient care in public and private hospitals as well as for all outpatient visits in public hospitals. All diagnoses were reported using ICD-9 up to 1996 where ICD-10 was used 19 . We identified all singleton children born from January 1, 1987 to December 31, 2001 who were still alive on January 1 st , 2006 yielding a total of 894,697 singletons.

The National Institute for Health and Welfare (THL), responsible for the Finnish Medical Birth Register and Finnish Hospital Discharge Register, gave permission to link and use encrypted health register data for this study. The data protection ombudsman was informed about the study, as requested by the national data protection regulation.

Exposure information

Antenatal care in Finland is tax-paid and offered to all pregnant women and care in low risk pregnancy includes approximately 10-14 visits. Data on maternal smoking came from concurrent information provided by pregnant women and systematically collected by midwives and public health nurses during the second trimester as part of routine antenatal care and archived in the FMBR. During the period from 1987 to 1990 responses were categorised as either non-smokers, smokers of less than 10 cigarettes per day, or 10 cigarettes or more per day. During the period 1991 to 2001 the average number of cigarettes per day was not collected, but replaced with information on whether or not women stopped smoking during first trimester. In the sibling matched analyses we defined pregnancy smoking as smoker and non-smoker and in mothers of children born 1991-2001 only those reported continued smoking as well as those only smoking during the first trimester were categorised as smokers.

Outcome definition

We studied children's entries in the FHDR until January 1 st , 2006 using ICD-10 diagnoses to identify children with HKD including hyperkinetic disorder (F90.0), hyperkinetic conduct disorder (F90.1) or other hyperkinetic disorder (F90.8 and F90.9) as endpoint in the analyses. We excluded 1901 children with pervasive developmental disorders, including autism, F84 (N=1095), mental retardation, F70-79, (N=262) and 325 with both these diagnoses. Further 219 children who had the ICD-9 (but not the ICD-10) diagnosis of 314 were excluded from the analyses, because the definition was not fully comparable with ICD-10.

Cohort definition

After the above exclusions the population included 892,796 children of whom 7,226 were diagnosed with HKD. There were 24,347 (3%) with missing smoking information, leaving 868,449 available for analyses, where 7023 children (0.8%) had HKD. Among the 443,076 boys there were 6013 (1.4 %) and among the 425,353 girls there were 1010 (0.2%) who received the HKD diagnosis over the observation period. The 513,198 participating women contributed with an average of 1.7 children to the entire cohort.

Statistical analyses

To control for differences length of follow up time we used Cox regression analysis, with child age as the primary time scale. To control for the increasing incidence of HKD over study time we adjusted for each year of birth as a categorical variable (1987-2001). We further a priori decided to adjust for child sex, gestational age at birth (less than 30, 30-33, 34-36,37-40,41 or more), maternal age (20 or less, 21-25, 26-30,31-35, 36 or more) and parity (0,1,2,3 or more). Data on maternal occupation was available and adjusted for in the period 1991 to 2001 and was transformed to an indicator of socioeconomic status (SES) according to a national system of classifications and standards in Finland 20 (upper white collar, lower white collar, blue collar, others). The analyses were performed using STATA 9.0. Hazard Ratios (HR) are presented with 95% confidence intervals (CI). Our analytic strategy was to analyze the entire population using regular cohort analyses and then to compare these findings with sibling-matched analyses.

Population cohort analyses

In the Cox regression model we assumed proportional rates for the exposure and the above mentioned potential confounders with one common baseline rate function. The proportional hazards assumption was evaluated for all variables by comparing estimated log-minus-log survivor curves over the different categories of variables investigated.

Because most women contributed to the cohort with more than one child we used robust standard errors to adjust the confidence intervals for the presence of siblings in the population analyses (declaring each of the sibling pairs to be a cluster). All analyses were repeated by sex and adjusted for the variables described above. Additionally in order to control for SES and because of change in exposure registration we separated the cohort into children born 1987-1990 and 1991-2001, where SES was available for the latter group.

Sibling matched analyses

We performed sibling-matched analyses to control for shared genetic and social confounding. We used stratified Cox regression with a separate stratum for each family identified by the mothers encrypted identification number. In the stratified Cox regression model each family have its own baseline rate function reflecting the family's shared genetic and social factors. The exposure comparisons, smoking versus non-smoking, are thus made within the family. We controlled for the same factors as in the cohort analyses, except for SES which is part of the shared social factors and therefore already controlled for in the sibling matched analysis. The stratified Cox regression model is an extension of the paired binomial model, taking differences in follow-up time into account. Thus only sibling pairs discordant for smoking as well HKD were 'informative', i.e. contributed information to the estimates. Indeed, the sibling without HKD should have at least as long follow-up time as the sibling with HKD to be informative.

Results

In the regular cohort analyses we found that children exposed to maternal smoking in pregnancy had about twice the risk of having a diagnosis of HKD during the up to 19 years of follow-up period (HR 2.01, 95% CI: 1.90-2.12). The results of the analyses in the two periods are shown in table 1. The analyses of children born 1987-1990 indicated the HKD risk increased by level of smoking. In a similar way the data for children born 1991-2001 suggested that those who quit smoking in early pregnancy had a slightly lower risk for HKD as compared with those who continued smoking beyond the first trimester, but this difference was not statistically significant. Excluding children born small for gestational age (

TABLE 1 about here)

The results comparing smokers with non-smokers in the full cohort and in the siblingmatched analyses are shown in Table 2. The adjusted analyses suggested a weak association between antenatal smoking exposure and HKD when boys and girls were analysed together and separately.

We finally analyzed possible birth order effects by stratifying the analyses by whether the smoking exposure was in the pregnancy of the older or the younger sibling and then whether the HKD diagnosis was given to the older or the younger sibling. The associations were similar for women smoking in the pregnancy of the older and the younger child (HR=1.3 and 1.2 respectively)

(TABLE 2 about here)

Discussion

In this cohort of the entire Finish population during a 15 year observation period we found in the cohort analysis that children prenatally exposed to maternal smoking had twice the risk of being diagnosed with HKD than children of non-smokers. This finding is in line with recent studies 21;22 a number of previous conventional case control and cohort studies that have reported a strong association between pregnancy smoking and various measures of the ADHD phenotype 11 as well as the diagnosis of HKD 10 .

However, in the sibling-matched analyses, when controlling for shared family confounders, the estimated association was much weaker. This finding indicates that a part of the association reported in most previous studies may be partly due to confounding as maternal smoking may be indicator of a genetic trait and social factors related to HKD.

These findings are in line with the findings of three recent studies.Thapar et al. used children born after different types of in vitro fertilization with egg-donation as a way to distinguish between genetic and exposure effects 15 . They found no association between smoking and the ADHD phenotype in genetically unrelated mother-child pairs which however could be due to chance by small sample size or that they had more girls among the offspring of exposed 23 . Two recent studies used the sibling design with endpoints of relevance for ADHD. D'Onofrio et al. studied the association between pregnancy smoking and hyperactivity problems based on parents answering three screening questions and found a considerable smaller effect using the sibling design as compared to the regular cohort analyses 16 . The same tendency was seen in a register based Swedish study, that studied the association between smoking in pregnancy in all Swedish children born 1987-2000 and prescription of ADHD medication in the year 2006 17 . In their sibling analyses they reported an estimate quite close to ours, but the crude proxy for ADHD, a one-year registration of prescription, does not capture older sibling treated medically early in life. This is quite important in the sibling design because discordant sibling pairs are misclassified as concordant and vice versa. The present study has a number of the strengths in being based on a complete 15 years follow-up using established diagnostic criteria based on clinical examination within in specialised departments within the public health service. We had practically complete follow-up data with little risk of selection bias, our data came from concurrently registered information rather than retrospective reports, and further our results were unlikely to be flawed by differential misclassification of HKD because children's care is universally available, publicity financed and organised in Finland. It is unlikely that the threshold for admission to hospital clinics is related to the prenatal smoking especially when siblings are compared.

The matched sibling design has a number of advantages in controlling for family factors. These family factors are difficult to measure and thus control for in conventional cohort designs. Full siblings share social environment but only half of their genes so even these analyses will tend to overestimate the tested association. One caveat of our study is that siblings were matched on mothers identification number and we did not have any information regarding fathers (due to strict data protection regulations in Finland). It may be the case that our estimates may overestimate the association and that even weaker associations had been found if we were able to identify and exclude half-siblings.

There are limitations to the sibling design that should be mentioned. The strict control for shared family factors limits the analyses to a small subset of the population. Only sibling pairs discordant for smoking as well as HKD contribute to the estimate in these analyses.

In the present study we had 40,615 sibling pairs, that were discordant for prenatal smoking exposure, but because discordance for HKD was also needed for a pair to be informative only 880 pairs contributed with information of the smoking-HKD association. In the adjusted stratified Cox regression model more sibling pairs discordant for some of the other factors in the model will principally add to the estimates, but the basic concept of this type of analyses can simply be illustrated by the ratio between the informative pairs supporting and discounting the hypothesis.

Positive association pairs (PAP) are sibling pairs that support a positive association between smoking and HKD i.e. where the mother smoked during the pregnancy of the child with HKD and did not smoke in the pregnancy with the child with without HKD. Negative association pairs (NAP) on the other hand were pairs where the mother did not smoke in the pregnancy of the child with HKD and smoked in the pregnancy of the child without HKD. To support the idea that prenatal smoking is a causal factor for HKD, one would expect more PAP than NAP, in fact twice as many to support the findings of most previous studies. Of the 880 pairs 484 pairs were PAP and 396 NAP with a ratio (1.2) very close to the results of the crude Cox regression analyses shown in Table 2. When restricted to comparison between boy siblings the PAP/NAP ratio was 1.3 (218/168) and restriction to in girl siblings this was 1.8 (45/25). Again the ratios are in line with the estimates for sibling matched Cox regression analysis and the small numbers explain the broad confidence intervals.

As illustrated above large register based studies are needed to gain valid estimates from sibling analyses. In this type of registers the information on smoking is collected routinely, but the smoking information is quite crude. The crude smoking information limits our ability to estimate effect of timing and dose. There are, however, further potential limitations to

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the interpretations of our results linked to the strict selection of smoking women in the sibling analyses. As mentioned above the sibling matched analyses are based on a subsample of smoking women and this sample may differ from the smoking women who were not informative in the sibling analyses. We therefore compared women reporting smoking and giving birth to their first child 1987-1991 according to whether they smoked in their next pregnancy. Among those, who smoked in both pregnancies 85% (95% CI: 84-86%) were smoking 10 cigarettes or more in the pregnancy of the first child as compared with 71% (95% CI: 70-72%) of subsequent non-smokers This indicates that there are more heavy smoking women among those who are not able to give up smoking in any of their pregnancies. Thus heavy smoking women are underrepresented in the sibling analysis and this may be part of the explanation for the attenuated estimates as compared with the regular cohort analyses.

It could further be argued that because information on smoking was based on personal contact between midwives/public health nurses and the pregnant women, the difference in unmatched and matched results could be due to misclassification of smoking status. Some misclassification seems likely and may be part of the explanation for the attenuation in our estimates when using sibling analyses. Women who contributed to the sibling analyses with informative siblings were characterised by having smoked in one pregnancy and by having a child with HKD. It is possible that women with HKD in the family may be more likely to under-report smoking If this bias is non-differential, which is expected, it would bias toward null-values and could partly explain the attenuation of the association. We were not able to evaluate this possibility directly because we did not have access to detailed smoking information, but we may evaluate this potential misclassification by looking at differences in birth weight between siblings with discordant smoking exposure.

The effect of antenatal smoking on birth weight is well established and if women contributing to our informative pairs more often under-reported true smoking in the subsequent pregnancy we would expect a smaller difference in birth weight between these sibling pairs compared with all sibling pairs discordant for smoking exposure. This was however not the case. We found no difference in the effect of smoking on birth weight. In the informative pairs adjusted for parity, gestational age at birth and gender there was a reduction of 88 grams (95% CI: 53-123 grams) in birth weight as compared with 69 grams (95% CI: 63-75 grams) in all the sibling pairs discordant for smoking. These differences in birth weight are in line with results from a recent report, where smoking information was validated against serum cotinine 24 . These findings speak against the possibility that the attenuation of the association was due to more misclassification of smoking status in the informative sibling pairs. By using a HKD diagnosis as the endpoint we had the possibility to study the more severe phenotype. A HKD diagnosis requires hyperactivity/impulsivity as well as inattention in at least two settings and is close to the DSM-IV ADHD-combined diagnosis. Although the Finnish register contains complete information for in-as well as outpatient contacts in the public health system, some children are unrecognized and thus untreated or treated without contact to the hospital system. Thus some cases of HKD or ADHD are undiagnosed in the hospital system but as they are few in the general population it will have little influence on estimation of the association we study. Even a low sensitivity will not bias our results as long as the specificity is high, which we find likely due to the use of strict diagnostic criteria in clinical practice in Finland. Differences in referral that in

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conventional studies may lead to bias, is less likely to do so in a sibling design because this bias is likely to be linked to the families. However, it is also possible that a diagnosis given to a child will make it more likely that an undiagnosed sibling with the disorder will be diagnosed. In the sibling design this would generate less discordant pairs but if linked to smoking attenuate the estimate.

In conclusion, previous reports may have overestimated the association between pregnancy smoking and HKD because they have not been able to control for shared family factors. We cannot completely discount the possibility that smoking is a causal factor, but then the size of the effect is probably smaller than what has previously been reported. Our findings are based on women, who were able to change smoking status between pregnancies and we probably cannot be extrapolated to women, who smoked in all their pregnancies. From a public health perspective, however, it is of interest to estimate if women, who manage to drop smoking in a pregnancy actually reduce their risk of getting a child with behavior problems. This study indicates that this may only be the situation for few.

Funding

Abstract

Background Studies have consistently shown that pregnancy smoking is associated with twice the risk of hyperactivity/inattention problems in the offspring. An association of this magnitude may make behavioral difficulties the most important health effect related to smoking during pregnancy. However, social and genetic confounders may fully or partially account for these findings.

Methods A cohort including all singletons born in Finland January 1, 1987 through December 31, 2001 was followed until January 1, 2006. We identified mothers with at least one child with HKD and a sibling discordant for prenatal smoking exposure. Data were available for 97% (N=868 449) and 880 sibling pairs were informative for the matched sibling analyses (one of the sibs exposed and one of the sibs had HKD).We used matched Cox regressions to estimate the association between prenatal exposure to smoking and HKD within these sibling pairs.

Results

We found a weak non-significant association between exposure to maternal smoking during pregnancy and risk for HKD in children using the sibling matched analysis (HR=1.20, 95% CI 0.97-1.49). In contrast, the general population estimate, without matching siblings, was in line with previous studies and substantially higher (HR 2.01, 95% CI: 1.90-2.12).

Conclusions Analysis using a matched sibling design resulted in a weaker and insignificant association between exposure to smoking during pregnancy and HKD than has been found in previous studies. We cannot completely discount the possibility that smoking is a causal factor, but then effect is probably small.

Keywords

BACKGROUND

Attention Deficit Hyperactivity Disorder (ADHD) defined by the DSM-IV criteria is one of the most common childhood psychiatric disorders 1 , with a cumulative incidence of 2-5% in Europe 2 . In the WHO diagnostic system (ICD-10) only children with the ADHD combined type (both inattention and hyperactivity/impulsivity symptoms) receive Hyperkinetic Disorder (HKD) diagnosis 3 , and is the focus of this study. Core symptoms are linked to poor school performance and other social problems 4 .

HKD has at least in part genetic causes 5 and brain imaging studies suggest that deviant brain morphology may be present already at birth 6 . Prenatal exposures have therefore been considered to be causally related to the disorder 7,8 . The association is biologically plausible and a number of animal studies, including studies on monkeys, suggest that prenatal exposure to nicotine may affect fetal brain development that mimics the disorder 9 .

A recent meta-analysis estimated a two-fold increased risk for the disorder in children of women who smoked during pregnancy 10 . An association of this magnitude may make behavioral difficulties the most important health effect related to smoking during pregnancy.

However, both smoking and HKD correlate with social conditions and mothers with attention problems may frequently be smokers 11 because nicotine improves attention 12 . It is therefore possible that smoking is an indicator of a genetic disposition to HKD and that the published associations reflect genetic and/or social confounding as indicated in a recent study 13 . They used an interesting design using children born after egg-donation as a way to distinguish between genetic and exposure effects 13 . Such alternative designs are needed, but their sample size was so small that the reported negative findings may be due to the limited information.

We estimated the association between prenatal smoking and HKD in the entire population of Finland born during a 15-year period using a discordant-sibling design, where siblings were discordant for both exposure to prenatal tobacco and HKD.

METHODS

Participants and outcome definition

Finland has a mandatory registration of all births into the Finnish Medical Birth Register (FMBR). The FMBR includes information on all pregnancies and births within the country. We identified all singleton children born from January 1, 1987 to December 31, 2001 who were still alive on January 1 st , 2006 yielding a total of 894,697 singletons. Data on maternal occupation was available for the period 1991 to 2001 and was transformed to an indicator of socioeconomic status (SES) according to a national system of classifications and standards in Finland 14 .

By using the unique personal identification number covering all residents in Finland, we were able to link the birth cohort with data from the Finnish Hospital Discharge Register (FHDR) including all inpatient (established in 1987) and all outpatient visits (established in 1998). Registration is mandatory for all inpatient care in public and private hospitals as well as for all outpatient visits in public hospitals. All diagnoses were reported using ICD-9 and since 1996 according to the ICD-10. We studied children's entries in the FHDR until January 1 st , 2006 using ICD-10 diagnoses to identify children with HKD including hyperkinetic disorder (F90.0), hyperkinetic conduct disorder (F90.1) or other hyperkinetic disorder (F90.8 and F90.9) as endpoint in the analyses. We excluded 1901 children with pervasive developmental disorders, including autism, F84 (N=1095), mental retardation, F70-79, (N=262) and 325 with both these diagnoses. Further 219 children who had the ICD-9 (but not the ICD-10) diagnosis of HKD were excluded from the analyses. In the remaining group of 892,796 children in the birth cohort, 7226 were diagnosed with HKD. There were 24,347 (3%) with missing smoking information, leaving 868,449 available for analyses, where 7023 (0.8%) children had HKD.

The 513,198 participating women contributed with an average of 1.7 children to the entire cohort.

For the sibling study we identified two groups of informative pairs, positive association pairs (PAP) and the negative association pairs (NAP). PAP were sibling pairs that support a positive association between smoking and HKD i.e. where the mother smoked during the pregnancy of the child with HKD and did not smoke in the pregnancy with the child with without HKD. Negative association pairs (NAP) were pairs where the mother did not smoke in the pregnancy of the child with HKD and smoked in the pregnancy of the child without HKD. If prenatal smoking is a causal factor for HKD one would expect more PAP than NAP. A total of 40,615 sibling pairs were discordant for prenatal smoking exposure, but because discordance for HKD was also needed for a pair to be informative only 880 pairs was left for the analyses, 484 pairs indicating a positive association and 396 indicating a negative association (table 2).

Exposure information

Antenatal care in Finland is tax-paid and offered to all pregnant women and care in low risk pregnancy includes approximately 10-14 visits. Data on maternal smoking came from concurrent information provided by pregnant women and systematically collected by midwives and public health nurses during the second trimester as part of routine antenatal care and archived in the FMBR . During the period from 1987 to 1990 responses were categorised as either non-smokers, smokers of less than 10 cigarettes per day, or 10 cigarettes or more per day. During the period 1991 to 2001 the average number of cigarettes per day was not collected, but rather replaced with information on whether or not women stopped smoking during first trimester.

In the sibling matched analyses we defined pregnancy smoking as smoker and nonsmoker and in mothers of children born 1991-2001 those who reported continued smoking or smoking only during the first trimester were categorised as smokers.

Statistical analyses

To control for differences in follow up time and the increasing incidence of HKD over study time we used Cox regression analysis. We adjusted for year of birth (1987-2001) In the population analyses we used robust standard errors to adjust the confidence intervals for the presence of siblings (stcox, vce). All analyses were repeated for each sex. SES was included in all analyses of children born between 1991 and 2001.

To control for common genetic and social confounding we performed sibling matched analyses. We used Cox regression (stcox, strata) matching siblings by the mothers encrypted identification number and controlled for the same factors as in the population analyses. The sibling-matched analyses were performed on all siblings but only sibling pairs discordant for smoking as well HKD were informative and contributed to the estimates.

Ethics

The National Institute for Health and Welfare (THL), responsible for the Finnish Medical Birth Register and Finnish Hospital Discharge Register, gave permission to link and use encrypted health register data for this study. The data protection ombudsman was informed about the study, as requested by the national data protection regulation.

RESULTS

Children exposed to maternal smoking in pregnancy had about twice the risk of having a diagnosis of HKD during the up to 19 years of follow up period. The analyses of children born 1987-1990 indicated the HKD risk increased by level of smoking (Table 1). In a similar way the data for children born 1991-2001 suggested that those who quit smoking in early pregnancy had a slightly lower risk for HKD as compared with those who continued smoking beyond the first trimester, but this difference was not statistically significant (Table 1). The analyses stratified for sex of the child suggested that the association was slightly stronger among girls than boys, but this difference did not reach statistical significance. Excluding children born small for gestational age or preterm did not change the results.

(TABLE 1 about here)

The results comparing smokers with non-smokers in the population and sibling-matched analyses are shown together in Table 2. There were slightly more Positive (PAP) than negative (NAP) and the PAP/NAP ratios were as expected in line with the unadjusted sibling matched analyses (Table 2). The adjusted analyses suggested a weak nonsignificant association between antenatal smoking exposure and HKD when both sexes were analysed together and separately. There was no overlap between the confidence intervals of the sibling-matched versus the population analyses when both sexes were analysed together and separately.

We analyzed possible birth order effects by stratifying the analyses by whether the smoking exposure was in the pregnancy of the older or the younger sibling and then whether the HKD diagnosis was given to the older or the younger sibling. The estimates were similar for women smoking in the pregnancy of the older and the younger (HR=1.3 and 1.2 respectively) as well as in pairs where the older sibling had HKD (HR 1.2) and where the younger was the child with HKD (HR=1.3)

(

DISCUSSION

Children prenatally exposed to maternal smoking had twice the risk of being diagnosed with HKD than children of non-smokers. However, in the sibling-matched analyses, the association was much lower. This finding suggests that a part of the association reported in the literature may be due to confounding by family factors that correlate with parental smoking.

The results of the population analyses are in line with a number of previous reports 10 including our own 15 which have addressed genetic confounding indirectly. Because parents with HKD may be more likely to smoke 16 made us and others question whether the smoking association is causal or spurious. 13 Maternal smoking may be an indicator of a genetic trait related to HKD and this heritable factor rather than smoking exposure per se may contribute to HKD in children. Our findings based on the sibling-matched analyses support this idea and is in line with a recent study by Thapar et al. who found significant association between smoking in pregnancy and offspring's ADHD behaviours as rated by mothers. This study was of particular interest because they used a design based on egg-donation pregnancies where mothers and children were genetically related and unrelated 13 . This quite innovative study leaves, however, questions still unanswered because it was based on a very small and selected sample and included twins. The present study has the strength of being based on a full population sample and thus a relatively large set of informative sibling pairs with the potential to partly control for heritable and social factors.

The present study has the strength of using the HKD diagnosis as endpoint in a large, complete population. In contrast to most previous follow up studies, we had practically complete data (97%), data based on concurrently registered information rather than based on retrospective reports, and further our results are unlikely to be flawed by selection bias 17 because care is tax-financed and universally available in Finland.

It can be argued that because information on smoking was based on personal contact between midwives/ public health nurses and the pregnant women, the difference in unmatched and matched results could be due to misclassification of smoking status. Women who contributed to the sibling analyses with informative siblings were characterised by having smoked in one pregnancy and by having a child with HKD. It is possible that smoking in subsequent pregnancies is under-reported. If this bias is nondifferential, which is expected, it would bias toward null-values and could partly explain the attenuation of the association. We examined this possibility by looking at differences in birth weight between siblings with discordant smoking exposure. If women contributing to our informative pairs more often under-reported true smoking in the subsequent pregnancy, we would expect a smaller difference in birth weight between these sibling pairs than between all sibling pairs discordant for smoking exposure. This was however not the case. We found no difference in the effect of smoking on birth weight. In the informative pairs adjusted for parity, gestational age at birth and gender a reduction of 88 grams (95% CI 53-123 grams) in birthweight as compared with 69 grams (95% 63-75 grams) in all the sibling pairs discordant for smoking. These differences in birth weight are in line with results from a recent report, where smoking information was validated against serum cotinine. 18 Therefore, our results are not likely to be due to misclassification of smoking status.

By using a HKD diagnosis as the endpoint we had the possibility to study the more severe and most common form of the DSM-IV ADHD-combined diagnosis. Others have compared the DSM-IV ADHD diagnosis with HKD 3 and the HKD diagnosis primarily identifies children with the most severe of the ADHD combined phenotype. We have also failed to identify all children with HKD. Although the Finnish register contains complete information for in-and outpatient contacts in the public health system, some children may be unrecognized and thus untreated or treated without contact to the hospital system. Thus some cases of HKD or ADHD will be misclassified because they are undiagnosed in the hospital system but as they are few in the general population it will have little influence on the association we study. Even a low sensitivity will not bias our results as long as the specificity is high, which we find likely due to the use of strict diagnostic criteria in clinical practice in Finland.

In conclusion, previous reports are likely to have overestimated the association between pregnancy smoking and HKD in the offspring and using the sibling design. We cannot completely discount the possibility that smoking is a causal factor, but this study indicates that the effect size is smaller than previously expected.

  Is maternal smoking during pregnancy a risk factor for Hyperkinetic disorder? -Findings from a sibling design.

  not change the results. Control for SES among children born 1991-2001 did only change the estimates slightly and the results were very similar in the two time periods.

Table 1

 1 The work was funded by the Nordic Council of Ministers research program 'Longitudinal Epidemiology' (020056), the Danish Research Council for Health and Disease (Obel) and VINMER (Rodriguez). Hazard ratio for Hyperkinetic Disorder (HKD) according to prenatal exposure for smoking. Children born in Finland 1987-2001 (N=868,449). All Cox regressions adjusted for robust standard error. All adjusted analyses are controlled for gender, year of birth, maternal age, gestational age at birth and parity. Adjusted analyses in children born 1991-2001 included adjustment for socioeconomic factors.

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	R
	e v
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	w
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	y

Table 2

 2

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	R
	e v
	i e
	w
	O n l
	y

Hazard ratio for Hyperkinetic Disorder (HKD) according to smoking during pregnancy. Children born in Finland 1987-2001 Cox regression analyses unmatched adjusted for robust standard error adjusting for sibling relations. Matched analyses on maternal encrypted identification number.

All adjusted analyses are controlled for gender, year of birth, maternal age, gestational age at birth and parity.

  The work was funded by the Nordic Council of Ministers research program 'Longitudinal Epidemiology' (020056), the Danish Research Council for Health and Disease(Obel) and VINMER(Rodriguez).

	F o r F o r F o r F o r
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	i e i e i e i e
	w w w w
	O n l O n l O n l O n l
	y y y y
	2

TABLE 2

 2

	about here)

Acknowledgements:

We thank Michael Rutter for valuable comments to earlier drafts of the manuscript, Petri Matveinen for the data linkages and final preparation of data for analyses and Therese Koops Grønborg for helping with the analyses.

Acknowledgements:

We thank Michael Rutter for valuable comments to earlier drafts of the manuscript, Petri Matveinen for the data linkages and final preparation of data for analyses and Therese Koops Grønborg for helping with the analyses.

Acknowledgements:

We thank Sir Michael Rutter for valuable comments on the manuscript, Petri Matveinen for the data linkages and final preparation of data for analyses and Therese Koops Grønborg for helping with the analyses.

Funding The work was funded by the Nordic Council of Ministers research program 'Longitudinal Epidemiology' (020056), the Danish Research Council for Health and Disease and VINMER.

Conflicts of interests: None declared

KEY Messages:

• In a matched sib-ship design we found a weaker association between smoking during pregnancy and a diagnosis of Hyperkinetic Disorder in the offspring than has been found in previous studies • The strong association found in previous studies may be due to confounding by social and genetic factors • Despite some limitations, the sib-ship design may provide an efficient design to control for confounding by family factors in studies of the effect of prenatal exposures.

Conflicts of interests: None declared

KEY Messages:

• In a matched sib-ship design we found a weaker association between smoking during pregnancy and a diagnosis of Hyperkinetic Disorder in the offspring than has been found in previous studies • The strong association found in previous studies may be due to confounding by social and genetic factors • Despite some limitations, the sib-ship design may provide an efficient design to control for confounding by family factors in studies of the effect of prenatal exposures.

O n l y


DDS Gerdien Telleman
email: g.telleman@kchir.umcg.nl

Gerry M Raghoebar

Arjan Vissink

Laurens Den Hartog

James Huddleston Slater

Henny J A Meijer

J J R Huddleston Slater

A systematic review of the prognosis of short (<10 mm) dental implants placed in the partially edentulous patient

Keywords: short dental implants, systematic review, partially edentulous, smoking, surface roughness dental implants, short implants, systematic review, partially edentulous, posterior zone, implant survival, implant length, surface topography, bone augmentation, smoking

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Short implants are increasingly used for the prosthetic solution of the extremely resorbed posterior zone of partially edentulous patients. However, there is no consensus in the literature on the definition of a short implant. Some authors consider 10 mm the minimal length for predictable success, so they consider any implant <10 mm in length as short [START_REF] Morand | The challenge of implant therapy in the posterior maxilla: providing a rationale for the use of short implants[END_REF]. Others defined an implant length of 10 mm also as a short implant (Das [START_REF] Neves | Short implants-An analysis of longitudinal studies[END_REF]. Because an implant can be placed at different levels a short implant has also been defined as an implant with a designed intra-bony length of 8 mm or less [START_REF] Renouard | Impact of length and diameter on survival rates[END_REF].

Several authors have given an overview of the literature of short implants in a narrative or structured review. [START_REF] Hagi | A targeted review of study outcomes with short (≤7 mm) endosseous dental implants in partially edentulous patients[END_REF] showed that, when applying 6 and 7 mm implants, short implants with press-fit shape and a sintered porous surface geometry revealed the best performance. Das [START_REF] Neves | Short implants-An analysis of longitudinal studies[END_REF] analyzed the treatment outcome of longitudinal studies using Brånemark and compatible implants of 7, 8.5 en 10 mm implants and concluded that short implants should be considered as a alternative treatment to advanced bone augmentation surgeries. [START_REF] Renouard | Impact of length and diameter on survival rates[END_REF] performed a structured review about the impact of implant length and diameter on survival rates in fully and partially edentulous patients and their review demonstrated a trend for an increase failure rate with short and wide-diameter implants. Two recent reviews have been published in which short implants were compared to conventional implants. [START_REF] Kotsovilis | A systematic review and meta-analysis on the effect of implant length on the survival of rough-surface dental implants[END_REF] concluded from their systematic review that the placement of short (≤8 mm or <10 mm) rough-surface implants is not a less efficacious treatment modality compared to the placement of conventional (≥10 mm) rough-surface implants. [START_REF] Romeo | The use of short dental implants in clinical practice: literature review[END_REF] concluded that the recent literature have demonstrated a similar survival rate for short and standard implants. But some important confounders need to be In the past short implants have been associated with lower survival rates [START_REF] Lee | Effect of implant size and shape on implant success rates: A literature review[END_REF][START_REF] Romeo | The use of short dental implants in clinical practice: literature review[END_REF]). There are several presumed reasons for a lower survival rate of short implants in the posterior maxilla or mandible. First, compared to longer implants with a comparable diameter there is less bone to implant contact when short implants are used, simply because there is less implant surface. Secondly, short implants are mostly placed in the posterior zone where the quality of the alveolar bone is relatively poor, especially in the maxilla (type III or IV, [START_REF] Lekholm | Patient selection and preparation. Tissue-integrated prostheses: osseointegration in clinical dentistry[END_REF]. Thirdly, often a very outsized crown has to be made to reach occlusion, because of the extensive resorption in the posterior region, which causes a higher (<1->2) crown to implant ratio. Crown to implant ratios between 0.5 and 1 were proposed to prevent peri-implant bone stress, crestal bone loss, and eventually implant failure [START_REF] Haas | Brånemark single tooth implants: A preliminary report of 76 implants[END_REF], Rangert et al. 1997[START_REF] Glantz | Biomechnical aspects of prosthetic implant-borne reconstructions[END_REF]. But the most recent systematic review on 2 studies on crown to implant ratios concluded that the ratio does not influence the peri-implants crestal bone loss [START_REF] Blanes | To what extent does the crown-implant ratio affect the survival and complications of implant-supported reconstructions? A systematic review[END_REF]).

To avoid the use of short implants the extremely resorbed bone can be augmented using a bone grafting technique. This modification in the patient's anatomy makes it possible to insert a longer implant, but an extra surgical intervention also leads to greater patient's morbidity, higher costs and a longer treatment period. [START_REF] Esposito | Interventions for replacing missing teeth: augmentation procedures of the maxillary sinus[END_REF] concluded from their systematic review on augmentation procedures of the maxillary sinus: "Short implants (5-8 mm) may be as effective and cause fewer complications than longer implants placed using a more complex technique." And from their systematic review on horizontal and vertical bone augmentation techniques for dental implant treatment they concluded (Esposito et To our knowledge, no systematic review with meta-analyses to determine the role of possible predictors has been performed on short (<10 mm) endosseous implants in the partially edentulous patients. Hence, the objective of this article was to systematically assess the clinical outcome of short implants (<10 mm) in partially edentulous patients and to evaluate the sources of heterogeneity between studies by subgroup analyses (viz. length, surface topography, smoking, implant location (mandible versus maxilla) and bone augmentation procedure).

Materials & methods

Data identification and selection

A MEDLINE and EMBASE search from January 1980 to October 2009 was conducted to identify studies on short endosseous implants in partially edentulous patients. In the present study an implant of length <10 mm was defined as a short implant, regardless the level of Two reviewers (GT and LDH) evaluated the relevance of studies by a first selection based on title and abstract. Disagreement about whether a study should be included for full inspection was resolved by a consensus discussion. Full-text documents were obtained for all possibly relevant articles. One reviewer (GT) read the full-text documents of all relevant articles and selected the articles for further methodological appraisal using the in-and exclusion criteria described below. To test the quality of the data extraction, a second reviewer (LDH) who was blinded to data extraction of the first reviewer, again extracted the data of a random subset of 25% of the included articles to see whether there was a consensus in extracting data. There was an excellent agreement between the two reviewers (kappa >0.95) for the extraction of the data.

Inclusion criteria:

-Study design: randomized controlled trial (RCT) or prospective cohort study -Patients: partially edentulous -Follow-up: >1 year -Study design: retrospective study, case report, review, non-clinical studies, explanation of technique or manual -Implants: (alumina)-zirconium implants or mini-implants for orthodontic anchorage -Suprastructures: cantilever constructions -Subjects: animals

Validity assessment

Two reviewers (GT and LDH) assessed the methodological quality using the forms 'quality assessment of a cohort study' and 'quality assessment of a randomized clinical trial' developed by the Dutch Cochrane Centre, a centre of the Cochrane Collaboration (tables 3 & 4). These two validity tools consist of 8 and 9 items, which have to be scored with a plus, minus or a question mark. It was decided that studies scoring four or more plusses were considered methodological acceptable. The two observers independently generated a score for the included articles. No blinding for author, institute or journal was performed.

Missing data

When not all needed data was given in the publication the author was sent an e-mail for further details. Non-responders were sent a reminder and a postal letter.

Statistical analysis

The pre-consensus degree of agreement between the two reviewers (GT and LDH) regarding eligible studies was expressed as a percentage of agreement of Cohen's unweighted kappa.

For each study the estimated failure rate per year and the estimated implant survival rate after 2 years (%) were assessed. In this systematic review an implant failure was defined as each implant from a cohort that was removed because of loss of integration, implant mobility, symptoms as pain, neuropathies, paresthesia or violation of the mandibular canal or psychological reason [START_REF] Albrektsson | The long-term efficacy of currently used dental implants; A review and proposed criteria of success[END_REF]). The estimated failure rate was calculated by dividing the number of events (implant failures) by the total implant exposure time. The total exposure time was calculated by taking the sum of [START_REF] Pjetursson | A systematic review of the success of sinus floor elevation and survival of implants inserted in combination with sinus floor elevation[END_REF]):

1. The exposure time of implants that could be followed for the whole observation time.

2. The exposure time up to a failure of implants that were lost during the observation time.

3. The exposure time up to the end of observation time for implants that did not complete the observation period due to reasons such as death, change of address, refusal to participate in the follow-up, chronic illnesses, missed appointments and work commitments. When the exposure time was not given separately for the short implants or the follow-up was not a closed period but had dispersal over years, a percentage (given by the number of short implants) of the total implant exposure time of all the implants was taken as the best available approximation. To exclude the studies just because their follow-up was not a closed period or also longer implants were studied was not preferred. For the calculation of the estimated survival rate after 2 years, the total number of events was considered to follow a Poisson distribution.

Summary estimates of the annual failure were calculated for different implant lengths in a stratified analysis. The different lengths of 5, 6, 7, 8, 8.5, 9 and 9.5 mm were studied. Sources of heterogeneity were explored using stratified analyses for the determinants surface topography, location (maxilla vs. mandible), smoking and bone augmentation procedures. The results of smooth turned surfaces were compared to roughened surfaces (i.e. dual acid-etched or titanium plasma sprayed) and the failures of short implants in the maxilla were compared to the mandible. Smokers were divided into two groups; 1) only non-smokers included in the study; 2) no restrictions about smoking habits; non-smokers, moderate and heavy smokers (≥15 cigarettes per day) were included in the study. Whether an augmentation procedure was performed simultaneously with placing the implant was scored as; 1) no augmentation procedure; 2) augmentation performed which might be either local sinus floor elevation surgery, a local covering of a fenestration of the implant surface or a local covering of an dehiscence of the implant surface.

In order to assess the heterogeneity of the included studies the Cochrane's Q statistic and associated P-value and the I 2 -test were calculated. I 2 quantified no heterogeneity by 0%, mild heterogeneity by <30%, moderate heterogeneity by 30-60% and notable heterogeneity by Two-year survival proportions were calculated via the relationship between estimated failure rate and survival function S, S (T) =exp(-T x failure rate), by assuming constant failure rates (Kirkwood & Sterne 2003). The 95% CI's for the survival proportions were calculated using the 95% confidence limits of the event rates.

Analyses were performed using the statistical software package 'Meta-analysis' (Comprehensive Meta-analysis Version 2.2, Biostat, Englewood NJ (2005), www.metaanalysis.com).

Results

Data identification and selection

The MEDLINE and EMBASE search identified 960 and 393 publications, respectively. A total of 164 publications was eligible for full text analysis. Checking references in the obtained literature did yield 1 additional publication [START_REF] Becker | Long-term evaluation of 282 implants in maxillary and mandibler molar positions: a prospective study[END_REF]). Of the 165 publications, 61 publications fulfilled the inclusion criteria. Methodological assessment of these 61 eligible publications revealed 39 methodologically acceptable publications. The inter-reviewer agreement on the methodological appraisal was measured with an unweighted kappa: 0.83. Disagreement was generally caused by slight differences in interpretation and was easily resolved in a consensus discussion. Unfortunately eight eligible articles had to be excluded from the meta-analysis because the contacted authors did not respond on either of the attempts for obtaining more details about the study. Furthermore, one author did not want Finally, a total of 29 publications was selected for data analysis. Figure 1 studies included a total of 2611 short implants (lengths 5, 6, 7, 8, 8.5, 9 and 9.5 mm). An overview of all studies included is given in table 1. This table is ranked by implant length (from 5 to 9.5 mm). A study can be mentioned twice or more times in table 1 as a variety of implant lengths can be used in a particular study, e.g. in the study of Corrente et al. 2009 10 implants of length 5 mm and 38 of length 7 mm were placed. The summary of the estimated survival rate after 2 years for the different implant length was 93.1% (95% CI: 79.7%-100%) for 5 mm, 97.4% (95% CI: 94.4%-100%) for 6 mm implants, 97.6% (95% CI: 96.3%-98.8%) for 7 mm implants, 98.4% (95% CI: 97.8 %-99.0%) for 8 mm implants, 98.8% (95% CI: 98.2%-99.6%) for 8.5 mm implants, 98.0% (95% CI: 96.4%-99.%) for 9 mm implants and 98.6% (95% CI: 94.6%-100%) for 9.5 mm implants.

Sources of heterogeneity between included studies

Sources of heterogeneity were explored in a sensitivity analysis with post hoc subgroups analyses. The main question behind these analyses was not to see if there were subgroups to F o r P e e r R e v i e w 13 be found, but merely to check whether results would change between these subgroups. These so called stratified analyses were run for implant surface topography (rough vs. machined), location (mandible vs. maxilla), smoking status (smokers were excluded vs. smokers were included) and augmentation procedure (not performed simultaneously with placing the implants vs. performed simultaneously with placing the implants). The overall results of all implant lengths showed a similar estimated failure rate for the different surface topographies 0.008 (95% CI: 0-0.010) for rough implants and 0.010 (95% CI: 0.005-0.016) for the machined implants, respectively. A difference of 29% between the two different surface topographies comparing to the summary of the estimated failure rate of all lengths of 0.007 (95% CI: 0.006-0.009). The estimated failure rate of implants placed in the maxilla was significant higher (0.010 (95% CI: 0.005-0.016)) as for implants in the mandible (0.003 (95% CI: 0.001-0.006)); a significant difference of 100%. The estimated failure rate from studies in which smokers were strictly excluded were twice as low (0.004 (95% CI: 0.000-0.007)) comparing in which heavy smokers (≥15 cigarettes per day) were also included (0.008 (95% CI: 0.004-0.013)); a difference of 57%. The difference in estimated failure rate in bone augmentation procedure simultaneously with placing the implants was not conspicuous. When there was not an augmentation procedure performed the estimated failure rate was 0.010 (95% CI: 0.006-0.013) comparing to when augmentation was performed 0.007 (95% CI: 0.004-0.010); a difference of 43%.

Heterogeneity was also calculated with the Cochrane's Q-test per implant length and of all lengths together (see table 2). All P-values were higher than the conventional cut point of 0.05, which indicated homogeneity of the different studies with one implant length and of all the studies together. The I 2 -test quantifies heterogeneity and for the implant lengths 5, 8.5, 9, 9.5 and of all lengths together there seems no heterogeneity, for implants length 6 and 8 mm

Discussion

This systematic review about short implants (<10 mm) in partially edentulous patients shows a (negative) significant association between failure rate and implant length; the longer the implant the higher the implant survival rate within the range of 5 to 8.5 mm length. The results for the shortest implants (5 mm, n=12) has to be considered with some caution, however, as only two studies were available [START_REF] Corrente | Short porous implants in the posterior maxilla: a 3-year report of a prospective study[END_REF], Deporter et al. 2001). This increasing survival rate with implant length was not reported in the systematic review of [START_REF] Kotsovilis | A systematic review and meta-analysis on the effect of implant length on the survival of rough-surface dental implants[END_REF] who found no statistical difference between short (≤8 or <10 mm) and conventional (≥10 mm) implants, but they did not perform a meta-regression analysis per implant length. Romeo et al. (2010) also found a similar survival rate for short and standard implants.

This review also shows that the estimated failure rates of studies in which short implants were placed in the mandible were lower than studies which placed short implants in the maxilla.

These results are in line with the treatment outcome of 'normal' length or standard implants, i.e. implants with a length >10 mm [START_REF] Friberg | Early failures in 4,641 consecutively placed Brånemark dental implants: a study from stage 1 surgery to the connection of completed prostheses[END_REF]. Moreover, implant failures of studies which excluded smokers were lower than the results of studies which included (heavy) smokers (≥15 cigarettes per day) patients. The association between smoking and implant failure, as found in the current review, could not always be shown in other studies. In the systematic review by [START_REF] Pjetursson | A systematic review of the success of sinus floor elevation and survival of implants inserted in combination with sinus floor elevation[END_REF] a difference in implant survival rate was found, but could not reach statistical significance. Also in line with standard length implants no difference in implant survival rate was observed between studies with and without (minor or major) augmentation procedures. The latter findings are consistent with the findings of who also reported that the survival percentages are comparable for implants placed in augmented bone or in non-augmented bone. In addition, in the current review also no difference between the survival rates of implants with a rough surface and with a smooth turned surface was noted. This is not consistent with the results of other studies specifically addressing this topic. Pjeturssson et al. (2008) reported in a systematic review significant better results for implants with a rough surface simultaneously placed with a sinus floor elevation. The systematic review on implant surface roughness and bone healing of [START_REF] Shalabi | Implant surface and bone healing; a systematic review[END_REF] presented a positive relationship between bone-to-implant contact and surface roughness. [START_REF] Wennerberg | Effects of titanium surface topography on bone integration; a systematic review[END_REF] concluded in their systematic review that surface topography (or surface roughness) does influence bone response at the micrometer level and might influence on a nanometer level. They also conclude that the majority of published papers present an inadequate surface characterization. This might be the reason why in the current study no difference in implant survival was found for the different surfaces. [START_REF] Wennerberg | Effects of titanium surface topography on bone integration; a systematic review[END_REF] wrote "a surface termed 'rough' in one study was not uncommonly referred as 'smooth' in another; many investigators falsely assumed that surface preparation per se identified the roughness of the implant".

The included studies were also checked for the outcome measure peri-implant bone loss, but unfortunately only 3 of the 29 selected studies reported data on per-implant bone loss around short implants (Deporter et 16 different length were included with an event rate of 4. This was insufficient data to do a metaanalysis. The rest of the used studies assessed in this review included single and multiple (splinted) tooth replacements. In the data presented in these studies no distinction was made between the implant-supported prosthetic rehabilitation and the removed implants, short implants could even be splinted to longer implants. This is a weakness of this systematic review, but one can assume that if there is severe peri-implantitis or loss of integration at one of a couple of splinted implants, it is best practice to remove this implant, otherwise the other implants might also be lost.

Our study is an implant based analysis, while we would have preferred to perform a patient based analysis, as events (implant loss) tend to cluster within the same patients. However, for this kind of analysis the data were not exactly enough described, which was partly due to the fact that most of the studies included in this review are not only about short implants.

Amongst others, we found some heterogeneity between studies, mostly due to the fact that most of the included studies were aggregated data sets. Some studies allowed to include certain groups (viz. smoking) whereas others excluded smokers. To precisely estimate the influence of such determinants (viz. smoking) one needs access to the original data sets in order to do the analyses on an individual level. It was, however, impossible to obtain all original datasets. To explore and to estimate the influence of the sources of heterogeneity we did a subgroup analysis. Although, point estimates of the calculated failure rates per implant length were different, the confidence intervals around these point estimates were comparable, when correcting for the normal finding that theses intervals were extended after subgroups analyses. Latter observations point to the conclusion that the heterogeneity is not enough to reject the results of the estimated failure rate per implant length. Our main outcome measure was the estimated implant survival rate after 2 years. We have chosen for a two year survival rate, as we tend to believe that after more than 1 year in function the implant survival rate as a function of time after loading has become rather constant [START_REF] Esposito | Biological factors contributing to failures of osseointegrated oral implants. (1) Succes criteria and epidemiology[END_REF]). To check this constancy we looked at studies with a follow-up up to one year and we estimated the survival rates after two years. From this calculations appeared very outranged numbers as 0.3 -12.0% survival rates. For this reason only studies with a mean follow up longer than one year were selected. The shortest mean follow up, included in this review, was 1.6 year. Our findings are confirmed by the prospective study of [START_REF] Cochran | A prospective multicenter 5-year radiographic evaluation of crestal bone levels over time in 596 dental implants placed in 192 patients[END_REF], who found in their radiographic evaluation of crestal bone the least bone loss between 1-year post-loading and the last 5-year recall. The most bone loss was found 6 months after implant placement.

Conclusion

The findings from this systematic review add to the growing evidence that short (<10 mm) implants can be successfully placed in the partially edentulous patients, though with a tendency of an increasing survival rate per implant length. Installation of short dental implants in the mandible has a better prognosis over installation in the maxilla. Furthermore the results of studies excluding smokers revealed higher implant survival rates than studies including heavy smokers (≥15 cigarettes per day). Surface topography and an augmentation procedure preceding the implant installation apparently could not be shown to affect the failure rate of short implants. Excluded articles: 32 methodologically unacceptable [START_REF] Farzad | Implant stability, tissue conditions, and patient self-evaluation after treatment with osseointegrated implants in the posterior mandible[END_REF] or incomplete data for meta-analysis [START_REF] Cecchinato | Submerged or non-submerged healing of endosseous implants to be used in the rehabilitation of partially dentate patients[END_REF] or study published twice in different articles [START_REF] Albrektsson | The long-term efficacy of currently used dental implants; A review and proposed criteria of success[END_REF] Additional articles from references n = 1 We are very happy that our paper, when complying to the minor comments of the referees, is suitable for publication in Journal of Clinical Periodontology. We have changed the manuscript according to the comments of the referees. The changes are highlighted in the text.

In detail:

Referee 1

The referee is right that our conclusion requires further refinement. It is indeed difficult to discern a true difference in % of the length as presented, although there is a tendency that survival increases with increasing implant length. See figure below. Therefore, as requested, we have made the conclusion of our paper more in line with the data provided: The findings from this systematic review add to the growing evidence that short (<10 mm) implants can be successfully placed in the partially edentulous patients, though with a tendency of an increasing survival rate per implant length.

Furthermore, the referee asked us to indicate whether the RCT under consideration in our review was randomized relative to the question under consideration. This was not the case. Therefore, we have added the next sentence:

The RCT included in this systematic review focused on submerged versus non-submerged healing of endosseous implants and not on implant length We feel that our manuscript has improved further and hope that it now will be accepted for publication in Journal of Clinical Periodontology.

Best regards, Also on behalf of the co-authors

  studies as they might be a key factor for the success in the use of short implants.

6 "

 6 al. 2010): Short implants appear to be a better alternative to vertical bone grafting of resorbed mandibles. Complications, especially for vertical augmentation, are common." New developments of the different implant systems, especially regarding the surface microtopography and chemistry, has resulted in higher survival rates of short implants (Romeo et al. 2010, Kotsovillis et al. 2009, Hagi et al. 2004, Renouard & Nisand 2006). The implant surface used to be a smooth turned surface, but nowadays different techniques, e.g., acidetching, grit blasting and titanium plasma spraying, altered the micro-topography of the implant surface by making the surface rougher. Applying such these techniques results in a tremendously enlarged implant surface. Recent developments are on the level of nanotopography (Meirelles et al. 2008, Meirelles et al. 2008).

  search strategy was set up in duplicate and independently by the first author and by an expert in searching literature databases. The electronic search was carried out by applying the following free text words and the applied thesaurus (MeSH): # 1 Search dental implant OR dental implants OR dental implantation OR endosseous dental implantation OR endosseous implant OR endosseous implants OR endosseous implantation, # 2 Search short* OR short-length OR short OR short length OR length, # 3 Search # 1 AND # 2 NOT (casereport OR case report OR case reports) NOT review NOT animal. To complete the search, we checked the reference lists in the obtained literature for additional relevant articles. No language restrictions were applied.

8 -

 8 Implant length: <10 mm -Minimum total number of short implants (<10 mm) placed in the assessed implant cohort of a particular study: 5 (When 2 implants of length 6 mm and 3 implants of length 7 mm were placed the study was also included) Exclusion criteria:

  errors were calculated to obtain 95% confidence intervals (CI's) of the estimated of the failure rates.

  in a reanalyses of his data. In addition, the data of one study was published twice, the data of the most recent publication was included[START_REF] Glauser | Immediate occlusal loading of Branemark TiUnite implants placed predominantly in soft bone: 1-year results of a prospective clinical study[END_REF][START_REF] Glauser | Immediate occlusal loading of Branemark System TiUnite implants placed predominantly in soft bone: 4-year results of a prospective clinical study[END_REF]).

  outlines the algorithm of the study selection procedure. The 29 eligible publications included a total of 28 prospective cohort and 1 randomized controlled trial (RCT). The RCT included in this systematic review focused on submerged versus non-submerged healing of endosseous implants and not on implant length. The mean follow-up of the 29 publications was 3.7 years (range 1.6-8.1 year). The first study was published in 1993, the latest in 2009. The median year of publication was 2003. The 29

  heterogeneity and for the group with implant length 7 mm there seems moderate heterogeneity.

  . (2000), Buser et al. (2002), Hämmerle et al. (2002) and Pjetursson et al. (2008)

  al. (2001), Deporter et al. (2001), Romeo et al. (2006)). There was also not enough data in the publications included to assess the determinant implant diameter in a subgroup analysis. Two studies, Mericske-Stern et al. (2001) and Polizzi et al. (2000), of the 29 included studies for this review were only about single tooth replacements. A total of 59 implants with

Figure 1 :

 1 Figure 1: Algorithm of study selection procedure

Table 3 :

 3 Quality assessment of a cohort study

	Item

Four or more plusses = methodologically acceptable

	F o r
	P
	e
	e r
	R
	e
	v i e
	w

Table 4 :

 4 Quality assessment of a randomized controlled trial (RCT)

	Item

Journal of Clinical Periodontology -PROOFJournal of Clinical Periodontology -PROOF

Acknowledgements

We gratefully acknowledge the assistance of Ms. S. van der Werf from the Groningen university medical library for her assistance in the elaboration of the search strategy.

Journal of Clinical Periodontology -PROOF Journal of Clinical Periodontology -PROOF Journal of Clinical Periodontology -PROOF Journal of Clinical Periodontology -PROOF