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View larger version:In a new windowDownload as PowerPoint SlideAdjusted models showing regression lines with 95% confidence intervals for outcomes by maternal age. Unintentional injury in children (quadratic model, 3 years), admission to hospital (linear models), complete immunisation (quadratic models, 9 months and 3 years), British ability scales naming vocabulary score (quadratic models), and total score on strengths and difficulties questionnaire (quadratic model, 3 years). Model coefficients, per 5 years of maternal age, are given with P values. Quadratic models are parameterised so that the coefficient for the linear component of maternal age (ß 1) gives the model slope at maternal age 30. MMR=measles, mumps, and rubella immunisation; BAS=British ability scalesUnintentional injuriesThe risk of unintentional injuries declined with increasing maternal age, with the final models for children aged 9 months, 3 years, and 5 years being linear, quadratic, and linear, respectively (figure).At nine months the risk of unintentional injuries declined across maternal age, with the risk in children of mothers aged 20 being 9.5%, decreasing to 6.1% for mothers aged 40. The model is quadratic for 3 year olds, showing a decline from 36.6% for mothers aged 20 to 28.6% for mothers aged 40.5 (where the curve reaches a minimum). The model is linear for 5 year olds, with risk decreasing from 29.1% for mothers aged 20 to 24.9% for mothers aged 40.Admissions to hospitalThe risk of children being admitted to hospital also declined with increasing maternal age, with the final models being linear in all cases (figure).At nine month, the probability of children being admitted to hospital declined from 16.0% when mothers were aged 20 to 10.7% when mothers were aged 40. For 3 year olds, the probability declined from 27.1% when mothers were aged 20 to 21.6% when mothers were 40. For 5 year olds, the change in hospital admissions with increasing maternal age was not statistically significant.ImmunisationsThe final models of complete immunisation rates by maternal age for 9 month olds and 3 year olds were quadratic (figure).At nine months the rate of complete immunisation increased with maternal age, from 94.6% when mothers were aged 20 to 98.1% when mothers were 40. At three years the maximum rate of complete immunisations was 81.3% when mothers were aged 27.3, with lower rates among younger and older mothers. Complete immunisations at three years, excluding combined measles, mumps, and rubella immunisation were also considered; the final model was linear, with no significant relation between immunisation rate and maternal age, indicating that non-linear effects are linked to take-up of the combined measles, mumps, and rubella immunisation.Children’s body mass index and overweightInitial models showed a significant positive association between the children’s body mass index and maternal age. However, once maternal body mass index was controlled for, no significant association with maternal age was found for either children’s body mass index or children’s overweight (table 2).Language development (British ability scales naming vocabulary)The final models of naming vocabulary score in relation to maternal age were quadratic, with scores increasing as maternal age increased (figure). At three years, the score for children of mothers aged 20 was 0.22 standard deviations below that for the children of mothers aged 40. At five years, the value for children of mothers aged 20 was 0.21 standard deviations below that for the children of mothers aged 40.Social and emotional difficultiesThe final models for the strengths and difficulties total problem score in relation to maternal age were quadratic at three years and linear at five years, with scores decreasing as maternal age increased, indicating better social development (figure). At three years, the score for children of mothers aged 20 was 0.28 standard deviations higher than for children of mothers aged 40, and at five years, the corresponding difference was 0.16 standard deviations.DiscussionIncreasing maternal age was associated with children having fewer hospital admissions and unintentional injuries, a greater likelihood of having had all of their immunisations by 9 months of age, better language, and fewer social and emotional difficulties. Such findings contrast with the known obstetric risks associated with older motherhood1 2 3 and serve as a counterpoint to evidence highlighting poorer health and developmental outcomes for children of younger mothers (<20 years).7 8 9 10 11 The positive findings in relation to increasing maternal age were generally consistent with the few other studies on children of older mothers, often defined as 40 years or older, which focused on other issues such as neurodevelopment, educational achievement, substance misuse, and juvenile crime12 rather than, as here, general health and development, both cognitive-linguistic and socio-emotional. There are, however, exceptions in the literature to the conclusion that older motherhood carries few risks for child functioning. One study of Israeli male adolescents showed poorer social and emotional functioning in association with both teenage mothers and mothers aged 40 or older at their child’s birth (relative to other mothers).13 Older mothers tend to be better educated, have higher family income, and be married, all factors associated with greater child wellbeing.7 28 Analyses controlled for these and other personal factors. Hence the results are indicative of associations with maternal age rather than covarying characteristics, or at least those included in this research. Also noteworthy in this study was the inclusion of children living in deprived neighbourhoods and experiencing high levels of family deprivation, as well as children representative of the general population, to increase the likelihood of identifying any adverse impacts. The fact that results were broadly similar for all outcomes when the analyses were undertaken separately for the population representative Millennium Cohort Study sample and the deprived National Evaluation of Sure Start sample indicates that these results are likely to be applicable across the spectrum of deprivation.The only health related outcome revealing any adverse relation with childbearing in older age was immunisation uptake by age 3 years, which declined with maternal age after age 33. This could have been a historical artifact, related to parental anxiety regarding now discredited claims linking the combined measles, mumps, and rubella with autism,29 which were prevalent in the media around the time of the birth and early years of the children studied here. It is possible that older mothers were more influenced by the media reports. Further analyses of immunisations excluding the combined measles, mumps, and rubella immunisation supported this interpretation as they revealed no relations between maternal age and uptake of all other immunisations.The likelihood of a child being overweight increased with increasing maternal age, but not when maternal body mass index was controlled for, indicating that this result was explained by greater maternal body mass index in older mothers, rather than by maternal age in itself. Nevertheless, this association is one that should be of concern for health practitioners.Strengths and limitations of the studyThis study has all the limitations of observational studies in attributing causality but does provide evidence relevant to an important clinical topic. Also, all covariates and some child outcomes apart from the children’s weight and height and naming vocabulary measurements were based on parental report; the fact that the data were collected in an optimal manner by direct parental interview with highly trained interviewers would seem to obviate somewhat the limitation. Although some child health information could have been extracted from medical records, that method also has pitfalls for data completeness and comparability. Error in measurement is always possible, but the measures taken were the best available and we have no reason to assume systematic mis-measurement, and if measurement error is not systematically related to a variable then measurement error decreases the likelihood of significant results. Inevitably some attrition occurred as the children aged and families withdrew or became non-contactable, but the attrition rates compare favourably with other longitudinal studies. Also, analyses were carried out in two ways, using only complete cases and using multiple imputation to include the full sample to deal with this issue. These two sets of analyses did not differ substantially. The initial hypotheses were tentative for the direction of effects owing to limited published evidence on the health of children born to older mothers. Finally, there was a shortfall in information on paternal age, as a significant proportion of children were living separately from their father. None the less, the large dataset, the representativeness of the samples, the powerful nature of the children’s outcomes, and the fact that data were collected originally for a different purpose improved the likelihood of the findings being valid. Also the fact that results were similar for all outcomes for separate analyses of the population representative Millennium Cohort Study sample and the deprived National Evaluation of Sure Start sample indicates that these results are likely to be applicable to the whole population and across the spectrum of deprivation.ConclusionIn contrast with the obstetric risks known to be associated with older motherhood these results indicate that increasing maternal age was associated with children having fewer hospital admissions and unintentional injuries, a greater likelihood of better protection from ill health through completed immunisations by age 9 months, better language development, and fewer social and emotional difficulties. The findings are noteworthy given the continuing increase in mean age of childbearing. It will be important to continue to examine relations between child outcomes and maternal age to see if the situation changes as the children age, and to explore possible mediating and moderating factors for the relations associated with maternal age. Possible mechanisms for the observed relations between child outcomes and maternal age might be environmental, such as differences in parenting, or genetic, as found for paternal age where the longer fathers and grandfathers waited to have children, the more likely it was for their offspring to live longer and healthier lives. This seemed to be due to longer telomeres of older fathers’ sperm, related to increased longevity and development, being inherited by offspring.30 Further research should explore possible mechanisms. Finally, the results of this study are relevant to concerns raised about older people seeking to use fertility treatments and possible risks posed to children delivered by older mothers.31What is already known on this topicEstablished risks associated with older maternal age (=40 years) include preterm labour, fetal malformation, fetal death, and increased risk of maternal cardiometabolic diseaseEvidence related to child health and development beyond the immediate postnatal period is lacking for the children of older mothersThere is an increased risk of deleterious consequences for children’s health and development associated with young motherhoodWhat this study addsIncreasing maternal age was associated with several beneficial effects on childrenChildren had fewer hospital admissions and unintentional injuries, a greater likelihood of being fully immunised by age 9 months, better language, and fewer social and emotional difficultiesNotesCite this as: BMJ 2012;345:e5116FootnotesWe thank the families and their children for their cooperation throughout both projects.Contributors: All authors helped to plan the research, and took part in the writing of the final article. JG undertook the statistical analyses, supervised by EM. EM had full access to all the data in the study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis. Funding: This research was funded by the Wellcome Trust through a grant entitled “Health of children born to older mothers”; the funding body had no involvement in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript. All authors are independent of the funding agency.Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; and no other relationships or activities that could appear to have influenced the submitted work.Ethical approval: This study was approved for both studies by the National Health Service South West multicentre research ethics committee (reference No MREC/01/6/65). Participants in both studies gave written informed consent.Data sharing: The data from the Millennium Cohort Study and the National Evaluation of Sure Start study are available from the Economic and Social Data Service (www.esds.ac.uk/).This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.References?Sutcliffe A, Baki Y. What is known about children born to older parents? In: Bewley S, Ledger W, Nikolaou D, eds. Reproductive ageing. Royal College of Obstetricians and Gynaecologists Press, 2009:173-82.?Berryman J, Thorpe K, Windridge K. Older mothers: conception, pregnancy and birth after 35. Pandora,1995. ?Vohr BR, Tyson JE, Wright LL, Perritt, RL, Li L, Poole WK. Maternal age, multiple birth, and extremely low birth weight infants. J Pediatr2009;154:498-503.OpenUrlCrossRefMedlineWeb of Science?Office for National Statistics. Birth statistics. Series FM1 No 35. ONS, 2007.?Statistics New Zealand.Births and deaths: year ended March 2011. 2012. www.stats.govt.nz/browse_for_stats/population/births/BirthsAndDeaths_HOTPYeMar11.aspx.?Martin JA, Hamilton BE, Sutton PD, Ventura SJ, Menacker F, Kirmeyer S, Division of Vital Statistics. Births: final data for 2004. National Vital Statistics Reports 55(1). US Department of Health and Human Services, Centers for Disease Control and Prevention, 2004.?Moffitt TE, E-Risk Study Team. Teen-aged mothers in contemporary Britain. J Child Psychol Psych2002;43:727-42.OpenUrlCrossRefMedlineWeb of Science?Botting B, Rosato M, Wood R. Teenage mothers and the health of their children. Popul Trends1998;93:19-27.OpenUrlMedline?Fraser AM, Brockert JE, Ward RH. Association of young maternal age with adverse reproductive outcomes. New Engl J Med1995;332:1113-7.OpenUrlCrossRefMedlineWeb of Science?Gilbert W, Jandial D, Field N, Bigelow P, Danielsen B. Birthoutcomes in teenage pregnancies. J Matern Fetal Neonatal Med2004;16:265-70.OpenUrlCrossRefMedline?Phipps MG, Blume JD, Demonner SM. Young maternal age associated with increased risk of postnatal death. Obstet Gynaecol2002;100:481-6.OpenUrlCrossRefMedlineWeb of Science?Fergusson DM, Woodward LJ. Maternal age and educational and psychosocial outcomes in early adulthood. J Child Psychol Psych1999;40:479-89.OpenUrlCrossRefMedlineWeb of Science?Weiser M, Reichenberg A, Werbeloff N, Kleinhaus K, Lubin G, Shmushkevitch M, et al. Advanced parental age at birth is associated with poorer social functioning in adolescent males: shedding light on a core symptom of schizophrenia and autism. Schizophr Bull2008;34:1042-6.OpenUrlFREE Full Text?Zammit S, Allebeck P, Dalman C, Lundberg I, Hemmingson T, Owen MJ, et al. Paternal age and risk for schizophrenia. Br J Psychiatry2003;183:405-8.OpenUrlFREE Full Text?Croen LA, Najjar DV, Fireman B, Grether JK. Maternal and paternal age and risk of autism spectrum disorders. Arch Pediatr Adolesc Med2007;161:334-40.OpenUrlCrossRefMedline?Dex S, Joshi H. Millennium cohort study, first survey: a user’s guide to initial findings. Centre for Longitudinal Studies, University of London Institute of Education, 2004.?Melhuish E, Belsky J, Leyland AH, Barnes J, National evaluation of Sure Start team. Effects of fully-established Sure Start local programmes on 3-year-old children and their families living in England: a quasi-experimental observational study. Lancet2008;372:1641-7.OpenUrlCrossRefMedlineWeb of Science?Noble M, Smith G, Penhale B, Wright G, Dibben C, Owen T, et al. Measuring multiple deprivation at the small area level: the indices of deprivation 2000. Regeneration research summary No 37. Department of the Environment, Transport and the Regions, 2000.?Plewis I. Millennium cohort study first survey: technical report on sampling. 4th ed. Centre for Longitudinal Studies, University of London Institute of Education, 2007. ?Irwin LG, Siddiqi A, Hertzman C. Early child development: a powerful equalizer. Final report for the World Health Organization’s Commission on the Social Determinants of Health. WHO, 2007. 2011. http://whqlibdoc.who.int/hq/2007/a91213.pdf.?Goodman R. The strengths and difficulties questionnaire: a research note. J Child Psychol Psychiatry 1997;38:581-6.OpenUrlMedlineWeb of Science?Elliott CD, Smith P, McCulloch K. British ability scales. 2nd ed. NFER-Nelson, 1996.?Centers for Disease Control and Prevention. Percentile data files with LMS values. CDC, 2010. ?Honaker J, King G, Blackwell M. Amelia II (R package) 2010. http://cran.r-project.org/web/packages/Amelia/index.html.?Rubin DB. Multiple imputation for nonresponse in surveys. Wiley, 1987.?Hesterberg T. Combining multiple imputation t, chi-square, and F inferences. Research report No 75. MathSoft, 1998.?Venables WN, Ripley BD. MASS (R package). http://cran.rproject.org/web/packages/MASS/index.html.?Kiernan KE, Mensah FK. Maternal indicators in pregnancy and children’s infancy that signal future outcomes for children’s development, behaviour and health: evidence from the Millennium Cohort Study. University of York, 2009. ?Centers for Disease Control and Prevention. Measles, mumps, and rubella (MMR) vaccine and autism fact sheet. CDC, 2007.?Eisenberg DTA, Hayes MG, Kuzawa CW. Delayed paternal age of reproduction in humans is associated with longer telomeres across two generations of descendants. Proc Natl Acad Sci USA2012: published online 11 June. ?Caplan AL, Patrizio P. Are you ever too old to have a baby? The ethical challenges of older women using infertility services. Semin Reprod Med2010;28:281-6.OpenUrlCrossRefMedline
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View larger version:In a new windowDownload as PowerPoint SlideFig 2 Predicted susceptibility to antiretroviral drugsThe prevalence of intermediate or high level resistance to nucleos(t)ide reverse transcriptase inhibitors other than zidovudine was less than 0.9%, reflecting the low frequency of multiple mutations in thymidine analogues. There was a comparatively high level of reduced susceptibility to recommended first line regimens of the non-nucleoside reverse transcriptase inhibitors efavirenz and nevirapine (3.7%). However, etravirine, a non-nucleoside reverse transcriptase inhibitor, displayed very low levels of resistance (0.4%), reflecting the lack of predicted effect of K103N. The potency of modern drugs from the protease inhibitor class was high (only 25 (1.1%) patients had substantially reduced susceptibility to any protease inhibitor), owing to the rarity of multiple protease mutations. These findings indicate that potent first line regimens can still be constructed from the original three drug classes for almost all patients.Prevalence of resistance in recently infected patientsBetween 2007 and 2009, 742 samples were linked to a recent infection test result, of which 171 (23.0%) were classified as recent. The overall prevalence of resistance did not differ significantly (P=0.66) between recent samples (20, 11.7%) or non-recent samples (60/571, 10.5%). Furthermore, we detected no significant differences in the prevalence of resistance by individual drug class (results not shown).DiscussionInterpretationThe previously observed decline in the prevalence of transmitted drug resistance in subtype B viruses seems to have been reversed for mutations associated with nucleos(t)ide reverse transcriptase inhibitors and protease inhibitors, despite an increase in the proportion of patients on antiretroviral therapy who are virologically suppressed (from 62% in 2000 to 84% in 20076). The most frequent mutations were T215 revertants, which may be transmitted as such or evolve from a virus harbouring a T215F or T215Y mutation.19 These and other mutations are associated with a significantly higher risk of virological failure than wild type genotypes.1 17 The prevalence of transmitted thymidine analogue mutations remained moderately high, despite a marked shift away from the prescribing in the UK of drugs that select for these mutations.One plausible explanation for this paradox is the onward transmission of resistant viruses from people who have not received antiretroviral therapy before and who were themselves infected with a resistant virus. This hypothesis is supported by a previous phylogenetic analysis of UK subtype B sequences, which described five transmission clusters comprised exclusively of patients with resistance mutations who are antiretroviral therapy naive.20 It was postulated that an increasingly greater proportion of transmitted HIV-1 drug resistance could originate from antiretroviral therapy naive lineages, and that there could ultimately be a limit in the decline of transmitted HIV-1 drug resistance.The first factor contributing to this possible limit is that people with undiagnosed HIV could disproportionally21 spread the epidemic, since they are more infectious in the period immediately after infection.22 Some studies23 24 (but not all25) have also shown that undiagnosed patients with HIV have more sexual partners than diagnosed patients. Furthermore, evidence is emerging that transmitted resistant viruses are more persistent than originally thought. The fitness cost (relative to wild type virus) of certain mutations, such as the T215 revertants and K103N, has been shown to be marginal in laboratory studies.26 27 Jain and colleagues provided clinical confirmation of this finding in a series of patients infected with resistant virus and who had two or more resistance tests before they started antiretroviral therapy.28 With the exception of the M184V mutation, which is highly replicatively deficient, all groups of transmitted mutations persisted beyond at least three years in the majority of patients.A second possible explanation for the continued prevalence of thymidine analogue mutations is that the use of tenofovir and abacavir are maintaining the prevalence of such mutations in patients who have received antiretroviral therapy despite the decline in the use of zidovudine and stavudine. Further phylogenetic research could shed light on the transmission dynamics of these mutations.Comparison with other studiesTwo recent studies have reported on time trends in transmitted HIV drug resistance. In a study conducted in 20 European countries between 2002 and 2006,29 Vercauteren and colleagues found a small, linear decline in levels of nucleos(t)ide reverse transcriptase inhibitor and protease inhibitor resistance; non-nucleoside reverse transcriptase inhibitor resistance was observed to increase followed by a decrease between 2004 and 2006. Bartmeyer and colleagues30 performed a similar analysis of a German seroconverter cohort between 1996 and 2007. In more recent years, resistance to nucleos(t)ide reverse transcriptase inhibitors seemed to be stable and resistance to non-nucleoside reverse transcriptase inhibitors seemed to increase, although clear patterns are difficult to discern due to the relatively small sample size.Study limitationsOur study has several limitations. Firstly, the analysis is based on resistance found at date of sample rather than date of infection. Since viral quasi-species harbouring resistance mutations may revert to, or be overgrown by, virus without the mutations,19 29 the true level of transmitted HIV drug resistance may have been under-estimated in this analysis. Also, the degree of this bias will be affected by the average time between HIV-1 infection and diagnosis, which may have changed over time. Furthermore, the diagnosis delay could mask the underlying trend in the prevalence of transmitted resistance by date of infection. However, we found no difference in the prevalence of resistance between recent and non-recent infections, in the subset of patients in which this analysis was possible. Secondly, the genotypic data analysed were generated by population sequencing with a limit of sensitivity of approximately 15 to 25%.31 32 Our estimates of the prevalence of transmitted HIV drug resistance may therefore be biased downwards. This will have also biased the type of mutations observed, with persistent mutations appearing to be more prevalent than those which rapidly become undetectable such as K65R or M184V. We do not consider this limitation to be a major concern, because the main objective of our study was to examine changes in the prevalence of transmitted HIV drug resistance over time. Another limitation was that our method of classifying treatment status could have resulted in misclassification bias if some patients who had received antiretroviral therapy were included in the analysis. Previous research by the UK HIV Drug Resistance Database has suggested that this effect could distort trends if there is misclassification in 4% or more of the samples analysed.33 Finally, as the prevalence of transmitted HIV drug resistance in subtype B viruses, the focus of this analysis, is known to be higher than that observed in other subtypes,34 our findings are not generalisable to the UK epidemic as a whole, although coverage of patients infected with subtype B virus is high.Conclusions and policy implicationsFinally, we consider the clinical implications of our main conclusion that resistant lineages may have become fixed in the circulating viral pool. This concept, if confirmed to be correct, will apply universally, particularly in countries where first generation nucleos(t)ide reverse transcriptase inhibitors continue to be used, and underscores the importance of sentinel surveillance. In terms of the UK (and probably other well resourced countries), the detectable mutations that tend to be transmitted should have little effect on nucleos(t)ide reverse transcriptase inhibitors currently used in first line regimens, that is, abacavir, tenofovir, lamivudine, and emtricitabine. Non-nucleoside reverse transcriptase inhibitors used in first line regimens are of greater concern, with approximately 4% of patients being infected with viruses with reduced susceptibility to efavirenz and nevirapine. Previous models7 have suggested that baseline resistance testing remains cost effective at the levels observed in this study. Therefore, our findings argue that testing at HIV diagnosis and continued monitoring should remain the standard of care.What is already known on this topicTransmitted HIV drug resistance can affect therapy successSome resistance mutations could persist more than others in the absence of selective drug pressure A 2007 paper has shown a reduction in transmitted drug resistance in the UK since 2005What this study addsTransmitted drug resistance is no longer declining in UK, and evidence suggests a sustained epidemic that is resistant to nucleos(t)ide reverse transcriptase inhibitors, irrespective of previous antiretroviral therapy useSusceptibility to antiretroviral therapy remains relatively high, and potent first line regimens can still be constructed from the original three drug classes for almost all patientsNotesCite this as: BMJ 2012;345:e5253FootnotesThe UK Collaborative Group on HIV Drug Resistance is a collaboration between the UK HIV Drug Resistance Database; UK CHIC; Health Protection Agency HARS; and participating academic centres, clinics, and laboratories.Analysis/writing group: David Dolling, Caroline Sabin, Valerie Delpech, Erasmus Smit, Anton Pozniak, David Asboe, Andrew Leigh Brown, Duncan Churchill, Ian Williams, Anna Maria Geretti, Andrew Phillips, Nicola Mackie, Gary Murphy, Hannah Castro, Deenan Pillay, Patricia Cane, David Dunn. David Dolling is the guarantor.Steering Committee: Celia Aitken, Gartnavel General Hospital, Glasgow; David Asboe, Anton Pozniak, Chelsea and Westminster Hospital, London; Clare Booth, Royal Free NHS Trust, London; Patricia Cane, Health Protection Agency, Porton Down; Hannah Castro, Jonathan Crofts, David Dunn (co-chair), David Dolling, Esther Fearnhill, Kholoud Porter, MRC Clinical Trials Unit, London; David Chadwick, South Tees Hospitals NHS Trust, Middlesbrough; Duncan Churchill, Brighton and Sussex University Hospitals NHS Trust; Duncan Clark, St Bartholomew’s and The London NHS Trust; Simon Collins, HIV i-Base, London; Valerie Delpech, Health Protection Agency, Centre for Infections, London; Anna Maria Geretti, University of Liverpool; David Goldberg, Health Protection Scotland, Glasgow; Antony Hale, Leeds Teaching Hospitals NHS Trust; Stéphane Hué, University College London; Steve Kaye, Imperial College London; Paul Kellam, Wellcome Trust Sanger Institute and UCL Medical School; Linda Lazarus, Expert Advisory Group on AIDS Secretariat, Health Protection Agency, London; Andrew Leigh-Brown, University of Edinburgh; Nicola Mackie, Imperial NHS Trust; Chloe Orkin, St. Bartholomew’s Hospital, London; Philip Rice, St George’s Healthcare Trust, London; Deenan Pillay (co-chair), Andrew Phillips, Caroline Sabin, University College London Medical School; Erasmus Smit, Health Protection Agency, Birmingham Heartlands Hospital; Kate Templeton, Royal Infirmary of Edinburgh; Peter Tilston, Manchester Royal Infirmary; William Tong, Guy’s and St. Thomas’ NHS Foundation Trust, London; Ian Williams, Mortimer Market Centre, London; Hongyi Zhang, Addenbrooke’s Hospital, Cambridge; Mark Zuckerman, King’s College Hospital, London.Centres contributing data: Clinical Microbiology and Public Health Laboratory, Addenbrooke’s Hospital, Cambridge (Jane Greatorex); HIV/GUM Research Laboratory, Chelsea and Westminster Hospital, London (Adrian Wildfire); Guy’s and St. Thomas’ NHS Foundation Trust, London (Siobhan O’Shea, Jane Mullen); HPA – Public Health Laboratory, Birmingham Heartlands Hospital, Birmingham (Erasmus Smit); HPA London (Tamyo Mbisa); Imperial College Health NHS Trust, London (Alison Cox); King’s College Hospital, London (Richard Tandy); Medical Microbiology Laboratory, Leeds Teaching Hospitals NHS Trust (Tony Hale, Tracy Fawcett); Specialist Virology Centre, Liverpool (Mark Hopkins, Lynn Ashton); Department of Clinical Virology, Manchester Royal Infirmary, Manchester (Peter Tilston); Department of Virology, Royal Free Hospital, London (Clare Booth, Ana Garcia-Diaz); Edinburgh Specialist Virology Centre, Royal Infirmary of Edinburgh (Jill Shepherd); Department of Infection and Tropical Medicine, Royal Victoria Infirmary, Newcastle (Matthias L Schmid, Brendan Payne); South Tees Hospitals NHS Trust, Middlesbrough (David Chadwick); St George’s Hospital, London (Phillip Hay, Phillip Rice, Mary Paynter); Department of Virology, St Bartholomew’s and The London NHS Trust (Duncan Clark, David Bibby); Molecular Diagnostic Unit, Imperial College, London (Steve Kaye); University College London Hospitals (Stuart Kirk); West of Scotland Specialist Virology Lab Gartnavel, Glasgow (Alasdair MacLean, Celia Aitken, Rory Gunson).Coordinating centre: Medical Research Council Clinical Trials Unit, London (Kate Coughlin, Jonathan Crofts, David Dolling, David Dunn, Esther Fearnhill, Kholoud Porter). Funding: This work was supported by the UK Medical Research Council (grant G0900274) and the European Community’s 7th framework programme (FP7/2007-2013) under the Collaborative HIV and Anti-HIV Drug Resistance Network (CHAIN; project 223131).Competing interests: All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: support from the UK Medical Research Council and the European Community’s 7th framework programme; no financial relationships with any organisations that might have an interest in the submitted work in the previous 3 years; and no other relationships or activities that could appear to have influenced the submitted work.Ethical approval: This study was approved by the UK multicentre research ethics committee and relevant local research ethic committees.Data sharing: No additional data available. 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