Tag Archives: Children

Long-term Psychological Effects of Exposure to War in Young People

In last fortnight’s news blog we examined the effect of exposure to war on subsequent mortality among children and found an eight-percent overall increased risk of child death during a year of conflict, and a 25% increase in children under the age of one in large conflicts.[1] I have now come across a further study that examines psychological outcomes after six years in a cohort of war exposed children (in effect child soldiers) from Northern Uganda.[2] Depression and anxiety are common sequelae of exposure to war and this study replicates this finding, but the cohort is large (n=539), so the study was able to explore the effects of different types of violence exposure. Threats to loved ones and witnessing violence were particularly toxic, as was sexual abuse in young girls. Duration of exposure was also very important. I was uncertain how war violence compares with other factors leading to depression and anxiety and whether the children had received any form of psychological intervention. It was difficult as a non-psychiatrist/psychologist to perceive what the associations meant in terms of severity, but the abuse of child soldiers was extreme and the results could possibly be interpreted as showing a degree of resilience. In any event this study adds to the previously cited article on the terrible human cost of war, beyond the direct effects.

— Richard Lilford, CLAHRC WM Director

References:

  1. Lilford RJ. Health Effects of Armed Conflict. NIHR CLAHRC West Midlands News Blog. 19 Oct 2018.
  2. Amone-P’Olak K, Otim BN, Opio G, Ovuga E, Meiser-Stedman R. War experiences and psychotic symptoms among former child soldiers in Northern Uganda: the mediating role of post-war hardships – the WAYS Study. Soc Psychiatry Psychiatr Epidemiol. 2014; 49(11): 1783-92.
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Health Effects of Armed Conflict: A Truly Fascinating Study

The phenomenon that more people die from the indirect effects of warfare than are killed directly is widely recognised. Wagner and colleagues studied the effect of armed conflict on child mortality in Africa.[1] They used a geospatial approach, linking georeferenced data on armed conflict to georeferenced data from the Demographic and Health Surveys. Their study covered two decades (1995-2015) and 35 African countries. The outcome variable was child survival to the age of one year. Overall, there was nearly an eight-percent increased risk of child death during a year of conflict. However, many of the conflicts were small, and the increased risk of death before the age of one year was over 25% for armed conflicts with more than 1,000 direct fatalities. The cumulative effect over eight years was up to four times higher than the contemporaneous increase, and the effect is greatly increased for long-lasting conflicts. There were significantly stronger effects in rural than in urban areas. The authors also examined child growth and found an increased risk of stunting in relation to conflict.

Sadly, there was no shortage of armed conflicts in the 35 African countries studied – 15,441 armed conflicts were recorded in the Uppsala Conflict Data Program over the two decades. The results reported here represent a massive burden of disease on a scale with malnutrition.

Avoiding conflict is a tricky subject, which lies outside the health domain, and which is discussed in Paul Collier’s book ‘The Bottom Billion’.[2] Conflict is also very strongly associated with national poverty, and generally the avoidance of conflict is, arguably, the biggest threat confronting humankind, as we will discuss in the future.

— Richard Lilford, CLAHRC WM Director

References:

  1. Wagner Z, Heft-Neal S, Bhutta ZA, Black RE, Burke M, Bendavid E. Armed conflict and child mortality in Africa: a geospatial analysis. Lancet. 2018; 392: 857-65.
  2. Collier P. The Bottom Billion: Why the Poorest Countries are Failing and What Can Be Done About It. Oxford: Oxford University Press; 2007.

Food Allergies and Childbirth

In a previous News Blog we looked at the practice of swabbing babies delivered via Caesarean section with vaginal fluid in an attempt to reduce the incidence of allergies in the child.[1] Another study has now been reported that could potentially strengthen this argument.[2] This was a nationwide cohort study conducted in Sweden that looked at over 1 million children, their route of delivery and the incidence of food allergies. Overall 2.5% of children were diagnosed with a food allergy, and this was positively associated with those who were delivered via C-section (hazard ratio 1.21, 95% CI 1.18-1.25) – both elective and emergency. Analysis of the data suggests that an extra 5 in 1,000 children delivered via C-section would develop a food allergy (compared to the reference group).

Interestingly there was also a negative association with those who were born prematurely (earlier than 32 weeks) (HR 0.74, 95% CI 0.56-0.98). The authors suggest this may be due to the postnatal care preterm infants receive, or is due to an immature gastrointestinal tract.

— Peter Chilton, Research Fellow

References:

  1. Lilford RJ. Exposure of the Baby to a Rich Mixture of Coliform Organisms from the Birth Canal. NIHR CLAHRC West Midlands News Blog. 22 April 2016.
  2. Mitselou N, Hallberg J, Stephansson O, Almqvist C, Melén E, Ludvigsson JF. Cesarean delivery, preterm birth, and risk of food allergy: Nationwide Swedish cohort study of more than 1 million children. J Allerg Clin Immunol. 2018.

Widespread Use of Antibiotics to Reduce Child Mortality

As discussed in our previous News Blog,[1] the rise in antibiotic resistance is a worrying situation, and it is widely recommended to limit the prescription of antibiotics to patients who are confirmed to have a treatable bacterial infection. However, a recent trial in three sub-Saharan African countries did the exact opposite with a mass distribution of azithromycin, a broad-spectrum antibiotic, to children under five with the aim of reducing child mortality.[2] This was a cluster-randomised trial of around 190,000 children in 1,533 communities of Malawi, Niger and Tanzania who were assigned to receive four biannual doses of antibiotic or a placebo. Overall, the mortality rate was 14.6 deaths per 1,000 person-years in areas that received the antibiotic, compared to 16.5 deaths in communities that received the placebo, while mortality was also 13.5% lower (95% confidence interval, 6.7-19.8) (p<0.001). The effect was greatest in the youngest sub-group of children, those aged between one and five months, with the authors estimating that one in four expected deaths were prevented due to administration of the antibiotic. There were no differences in serious adverse events within a week of administration. If this strategy was to be more widely rolled out, one approach to combat resistance developing would be to limit it to the populations most in need and only for a short time.[3]

— Peter Chilton, Research Fellow

References:

  1. Chilton PJ. Non-Antibiotic Medicines May Increase Antibiotic Resistance. NIHR CLAHRC West Midlands News Blog. 18 May 2018.
  2. Keenan JD, Bailey RL, West SK, Arzika AM, for the MORDOR Study Group. Azithromycin to Reduce Childhood Mortality in Sub-Saharan Africa. New Engl J Med. 2018; 378: 1583-92.
  3. Maxmen A. Giving at-risk children pre-emptive antibiotics reduces deaths. Nature. 25 April 2018.

Another Spectacular Study Based on Demographic and Health Surveys

Under five mortality has dropped sharply around the world in the last few decades.[1] For example, in sub-Saharan Africa mortality for children aged 1-5 dropped from 42.7 per thousand in 2002-08 to 22.0 per thousand in 2009-14. The situation in twins was recently investigated using data from 90 Demographic and Health surveys across no less than 30 countries.[2] The decline in mortality was much less steep among twins than among singleton live births.

Twins are very vulnerable and have benefited less than singletons from the reduction in child mortality. Clearly, this group of vulnerable people needs special attention.

— Richard Lilford, CLAHRC WM Director

Reference:

  1. UNICEF. Under-Five Mortality. 2018.
  2. Monden CWS, Smits J. Mortality among twins and singletons in sub-Saharan Africa between 1995 and 2014: a pooled analysis of data from 90 Demographic and Health Surveys in 30 countries. Lancet Glob Health. 2017; 5: e673-9.

What Do You Think When You Hear ‘Scientist’?

If you have spent much time in universities you may have seen various stickers or leaflets raising awareness of campaigns that support women in STEM fields (science, technology, engineering and mathematics). There has been a push in recent years to get more girls and women into STEM subjects. Fifty-two percent of those who graduated in STEM disciplines in 2014 were female.[1] This varies widely between disciplines though, with females making up around 80% of graduates in subjects allied to medicine or veterinary sciences, but only around 15% in computer science or engineering and technology. While the gender balance of all STEM graduates are roughly equal, this is not reflected in employment however, with figures suggesting around 23% of employees in UK STEM industries are female,[1] while data from the UNESCO Institute for Statistics less than 30% of scientific researchers worldwide are female.[2]

Does the future hold more promise? A meta-analysis by Miller and colleagues looked at fifty years worth of studies where school children were asked to draw a scientist and examined the genders depicted.[3] They found that over time the percentage showing female scientists has increased – from 0.6% in data collected in 1966-77 to around 40% in 2015. However, when looking at the age of children (in studies since the 1980s) they found that while there was roughly equal representation of male and female scientists among 5 and 6 year olds, by the age of 7-8 years significantly more men were drawn. In the drawings made by girls only, the switch from predominantly female to male depictions happened around 10-11 years. Perhaps with an increase in female representation in STEM roles, especially in public, then young girls might be more likely to see themselves in such a field and thus increase the proportion in the workplace. Equally more needs to be done to emphasise gender equality at these key developmental milestones.

— Peter Chilton, Research Fellow

References:

  1. WISE Campaign for Gender Balance in Science, Technology & Engineering. Women in STEM workforce 2017. 24 October 2017.
  2. UNESCO Institute for Statistics. Women in Science. Fact Sheet No. 43. March 2017.
  3. Miller DI, Nolla KM, Eagly AH, Uttal DH. The Development of Children’s Gender-Science Stereotypes: A Meta-analysis of 5 Decades of U.S. Draw-A-Scientist Studies. Child Development. 2018.

Immunisation Against Rotavirus: At What Age Should it be Given?

A three way RCT [1] from Thailand shows that rotavirus vaccine is effective in reducing the incidence of diarrhoea in children (which we know), and that a neonatal schedule is no less effective and probably more effective than an infant schedule. Giving the vaccine early may reduce the risk of intussusception – apparently a risk with the infant schedule.

— Richard Lilford, CLAHRC WM Director

Reference:

  1. Bines JE, At Thobari J, Satria CD, et al. Human Neonatal Rotavirus Vaccine (RV3-BB) to Target Rotavirus from Birth. New Engl J Med. 2018; 378(8): 719-30.

The Health Economics of Infertility Treatment

Recently I found myself holding forth on the above topic in a plenary talk at the International Federation of Fertility Societies combined meeting with the African Fertility Society in Kampala. I made the point that the health economics of infertility raises a number of issues that are not generally considered in the standard canon for health economic assessment of health technology assessments (HTA).[1] Four issues stand out:

  1. The benefits of infertility treatment are more difficult to capture on a single quality of life (QoL) scale than in the case for standard HTA.
  2. The standard practice of discounting benefits can be questioned.
  3. The beneficiaries are more diverse, potentially extending to many family members.
  4. The issue of whether the lifelong utility of the potential child should be include is controversial.

I shall briefly consider these in turn.

  1. Benefit – generic quality of life (QoL) scales do not seem up to the job. First, it is very difficult to capture the benefits over a lifetime. The ‘area under the curve’ is the important relevant quantity and this is not well captured in cross-sectional studies. Second, QoL deteriorates when a sub-fertile couple have a baby, as it does for fertile people. I discovered this many years ago in a collaborative study with the Health Economics department at the University of York (unpublished). This finding reinforces the importance of a lifetime perspective. Third, it is doubtful that maximisation of the dimensions captured in a generic QoL scale are the things that people wish to maximise when they decide to have children – there is a deeper purpose in play. So, a utility function based on a direct trade-off would be preferable to a standard generic QoL scale, such as the SF-12 or EQ-5D. This way, the respondent can take a lifetime perspective and factor in all the valued benefits and disbenefits of treatment. Torrance used a standard gamble on a large study of US citizens and measured a disutility of 0.07 (utility 0.93).[2] That is to say, the average respondent would run up to a 7% risk of death to enable them to have a first child. Such a standard gamble method would likely underestimate the utility loss for those who actually experience infertility for reasons David Arnold and I explicated elsewhere.[3] A perhaps better method to capture the benefit over a lifetime would be willingness-to-pay studies and here, in addition to studies at the population level (say using discrete choice methods), studies of revealed preferences are possible. This is because much IVF takes place in an entirely private market. This enables the ‘market clearing’ price for infertility services to be observed (ideally in relation to disposable income). The high proportions of disposable incomes infertile people allocate to infertility treatment, sometimes amounting to catastrophic losses,[4] provides some evidence that Torrance’s study underestimates the trade-offs people will make in order to have children.
  2. Choice of discount rate – The fact that benefits continue to accrue, and may increase, over time, suggests that discounting may not be normative. Given that disbenefits generally precede benefits, it makes little sense to discount from the point of intervention. That said, it is important to factor disbenefits of treatment and downstream costs into the analysis. Disbenefits include the cost and discomfort of treatment and knock-on costs, for example, resulting from an increased risk of prematurity. Conversely, there may be hidden benefits beyond the joys of parenthood – for example, in reduced Intimate Partner Violence.[5]
  3. Diverse beneficiaries – In ‘normal’ health economics, benefits are hypotheticated on the affected person, even though loved ones also stand to benefit. Loved ones benefit through the improved health of the affected person. Ignoring third party benefits can be condoned on the ‘level playing field’ principle – in a comparison across diseases of middle-age, beneficiaries of various alternative treatments are in a roughly similar position – they have similar numbers of loved ones on average. On this basis, the decision tree can be ‘pruned’. It could be argued that this argument breaks down when comparisons are made across generational lines. In the particular case of infertility, mothers and fathers get direct benefits, as do grandparents and others, not only through the ‘affected’ person, but directly from the child that results from the treatment. For instance, the father is just as much a beneficiary as the mother. Grandparents are not far behind – I can attest to that. On the other hand, factoring these beneficiaries into the equation seems to tilt the playing field too far the other way, i.e. towards infertility services. Factoring the benefits that accrue to all these people would weight services for children in general, and infertility services in particular, very strongly. This is a topic requiring more philosophical analysis and, perhaps, empirical investigation.
  4. What about the child who would otherwise not have existed – the question of the utility of the hypothetical lives is vexed. Certainty, no-one counts the utility loss from contraception, even when no later ‘replacement child’ is envisaged. On the other hand, the utility of neonatal survival is included in standard economic practice. My preference is not to include this utility, but I am hard-pressed to defend this on a bottom-up, philosophical basis. Richard Hare, the famous Oxford philosopher, did attempt such an analysis and his conclusions support my instinct. Certainly, including the lifetime utility of the child massively improves the cost-benefit ratio of infertility services,[6-8] and if the tax return from the child is included, then a treatment such as IVF becomes a ‘no-brainer’ since it ‘dominates’ – it saves money and yields benefit down to a very low success rate (<6% of so).[9]

What would happen if we:

  1. Accepted a utility function of 0.9 (close to that of Torrance).
  2. Ignored other beneficiaries, including the child?

We present such an analysis below. Even under these relatively conservative constraints, IVF is cost-effective in most countries, and could be cost-effective in LMICs if some new idea, such as incubation within the vagina, were used.

Say we gave infertility a disutility of 0.1 over 50 years, undiscounted.
Then, the utility in an infertile couple successfully treated = 5 QALYs undiscounted and 1.1 discounted at 3%.
Let’s say society will pay $100 per QALY.
Then a treatment with a 25% success rate can have a net cost of up to $125 undiscounted, but less than $28 discounted.

— Richard Lilford, CLAHRC WM Director

I thank Sheryl van der Poel for sending some of the references quoted in this article.

References:

  1. Drummond MF. Methods for the economic evaluation of health care programmes. Oxford: Oxford University Press. 2005.
  2. Torrance GW. Measurement of Health State Utilities for Economic Appraisal. J Health Econ. 1986; 5: 1-30.
  3. Arnold D, Girling A, Stevens A, Lilford R. Comparison of direct and indirect methods of estimating health state utilities for resource allocation: review and empirical analysis. BMJ; 2009; 339: b2688.
  4. Wu AK, Odisho AY, Washington III SL, Katz PP, Smith JF. Out-of-Pocket Fertility Patient Expense: Data from a Multicenter Prospective Infertility Cohort. J Urology. 2014; 191(2): 427-32.
  5. Stellar C, Garcia-Moreno C, Temmerman M, van der Poel S. A systematic review and narrative report of the relationship between infertility, subfertility, and intimate partner violence. Int J Gynecol Obstet, 2016; 133: 3-8.
  6. Connolly MP, Pollard MS, Hoorens S, Kaplan BR, Oskowitz SP, Silber SJ. Long-term Economic Benefits Attributed to IVF-conceived Children: A Lifetime Tax Calculation. Am J Manag Care. 2008; 14(9): 598-604.
  7. Svensson A, Connolly M, Gallo F, Hägglund L. Long-term fiscal implications of subsidizing in-vitro fertilization in Sweden: A lifetime tax perspective. Scand J Pub Health. 2008; 36: 841-9.
  8. Fragoulakis V & Maniadakis N. Estimating the long-term effects of in vitro fertilization in Greece: an analysis based on a lifetime-investment model. Clinicoecon Outcomes Res. 2013; 5: 247-55.
  9. Baird DT, Collins J, Egozcue J, et al. Fertility and Ageing. Hum Reprod Update. 2005; 11(3): 261-76.

Involving Families in Neonatal Care

It is an unfortunate fact that some children need to be admitted into a neonatal intensive care unit (NICU) soon after birth, and this physical separation can often impact on the physical, psychological and emotional health of both the parents and the babies. In many NICUs the parents are expected to take a step back, with NICU staff providing the great majority of day-to-day care of the baby. An alternative approach, that is not widely used, is the Family Integrated Care (FICare) programme, which facilitates collaboration between parents and the NICU staff. Parents become involved in all aspects of their baby’s care, such as feeding, changing, bathing, as well as decision-making and taking part in medical rounds. A recent paper in the Lancet Child and Adolescent Health looked at the effectiveness of an FICare programme in 26 NICUs in Canada, Australia and New Zealand.[1] Premature babies (born at 33 weeks or earlier) were randomly assigned to receive standard NICU care (n=891), or be provided with FICare (n=895). Parents in the FICare group had to commit to be present for at least six hours each day, attend educational sessions, and provide active care for their baby. At 21 day follow-up the babies in the FICare group had significantly greater weight gain and an average daily weight gain of 26.7g (vs. 24.8g) (both p<0.0001). Mothers in the FICare group also had significantly higher rates of exclusive breastmilk feeding (p=0.016).  Further, parents had significantly lower scores on mean levels of stress (p<0.00043) and anxiety (p=0.0045). There were no significant differences in mortality, major morbidity, oxygen therapy duration, or length of hospital stay.

— Peter Chilton, Research Fellow

Reference:

  1. O’Brien K, Robson K, Bracht M, et al. Effectiveness of Family Integrated Care in neonatal intensive care units on infant and parent outcomes: a multicentre, multinational, cluster-randomised controlled trial. Lancet Child & Adol Health. 2018.

Risks of Children Using Technology Before Bed

We live in an increasingly technologically connected society, which even extends to children – for example, 74% of children (9-16 years old) in the UK use a mobile phone, with most receiving their first phone at the age of 10 years old;[1] while around half have a television in their bedroom at age 7.[2] For many it can be difficult to switch off at the end of the day – the allure of one more video, or another scan of social media can be strong. As such, many children use technology at bedtime, which may impact on their sleep as the light emitted by these devices has a higher concentration of ‘blue light’, which affects the levels of melatonin, a sleep-inducing hormone.[3] Previous research has shown the importance of sleep on children’s health and behaviour, and so Fuller and colleagues conducted a study looking at use of technology at bedtime and its effects on various health outcomes.[4] They surveyed 207 parents of 8-17 year olds and found that children who watched television at bedtime were significantly more likely to be overweight or obese than those who did not (odds ratio 2.4, 95% CI 1.35-4.18). Similar results were found for children who used a phone at bedtime (OR=2.3, 95% CI 1.31-4.05). There were no significant differences seen with computer or video game use. The authors also looked at sleeping behaviour and found a significant relationship between average hours of sleep and bedtime use of television (P=0.025), phone (P<0.001), computer (P<0.001), and video games (P=0.02). Further analysis showed that children who used various technologies were also more likely to be tired in the morning, less likely to eat breakfast, and more likely to text during the middle of the night. The authors recommend setting up ‘tech-free’ zones and making sure that devices are charged outside of the child’s bedroom.

Of course, this study only shows an association – it may be that some children have difficulty getting to sleep and so turn to technology in order to help them drift off. Meanwhile, the study is subject to reporting bias from the self-reported surveys of the parents, and so further studies are needed.

— Peter Chilton, Research Fellow

References:

  1. GSMA report. https://www.gsma.com/publicpolicy/wp-content/uploads/2012/03/GSMA_Childrens_use_of_mobile_phones_2014.pdf. 2014.
  2. Heilmann A, Rouxel P, Fitzsimons E, Kelly Y, Watt RG. Longitudinal associations between television in the bedroom and body fatness in a UK cohort study. Int J Obes. 2017; 41: 1503-9.
  3. Fuller C, Lehman E, Hicks S, Novick MB. Bedtime Use of Technology and Associated Sleep Problems in Children. Glob Pediatr Health. 2017.
  4. Schmerler J. Q&A: Why Is Blue Light before Bedtime Bad for Sleep? Scientific American. 01 September 2015.