In 2019, the global age-standardized death rate for Down syndrome was around 0.3 per 100,000 population. The most common cause of death for adults and children with Down syndrome is respiratory infection. This statistic shows the age-standardized death rate for Down syndrome worldwide in 1990 and 2019, by gender.

Background. Downs syndrome (DS) is the commonest of the congenital genetic defects. Its incidence has been rising in recent years for unknown reasons. Objective. Investigate the relationship of DS to substance- and cannabinoid- exposure; and causality.

Methods. Observational ecological population-based epidemiological study 1986-2016. Analysis performed January 2020. Geotemporospatial and causal inference analysis.

Participants: Patients were diagnosed with DS and reported to state based registries; collated nationally. Data source: annual reports of National Birth Defects Prevention Network of Centres for Disease Control.

Exposures: Drug exposure was taken from the National Survey of Drug Use and Health (NSDUH) conducted annually by Substance Abuse and Mental Health Services Administration. Nationally representative sample 67,000 participants annually. Drug exposures: cigarette consumption, alcohol abuse, analgesic/opioid abuse, cocaine use and last month cannabis use. Ethnicity and median household income: US Census Bureau. Maternal age of childbearing: CDC births registries. Cannabinoid concentrations: Drug Enforcement Agency seizures.

Results. NSDUH report 74.1% mean annual response rate. All other data was population-wide. DS rate (DSR) was noted to be rising over time, cannabis use, and cannabis-use quintile. In the optimal geospatial model lagged to four years terms including Δ9-tetrahydrocannabinol and cannabigerol were significant (from β-est.=4189.96 (95%C.I. 1924.74, 6455.17), P=2.9x10-4). Ethnicity, income, and maternal age covariates were not significant. DSR in states where cannabis was not illegal was higher than elsewhere (β-est.=2.160 (1.5, 2.82), R.R.=1.81 (1.51, 2.16), P=4.7x10-10). In inverse probability-weighted mixed models terms including cannabinoids were significant (from β-estimate=18.82 (16.82, 20.82), P

Conclusions. Our data show that the association between DSR and substance- and cannabinoid- exposure is robust to multivariable geotemporospatial adjustment, implicate particularly cannabigerol and Δ9-tetrahydrocannabinol, and fulfil causal crietria. Cannabis legalization was associated with elevated DSR’s. These findings are consistent with those from Hawaii, Colorado, Canada and Australia and concordant with several cellular mechanisms. Given that the cannabis industry is presently in a rapid growth-commercialization phase the present findings linking cannabis use with megabase scale genotoxicity suggest unrecognized DS risk factors, are of public health importance and suggest that re-focussing the cannabis debate on multigenerational and intergenerational health concerns is prudent.

Non-Invasive Prenatal Testing Kit Market Outlook

The global market size for Non-Invasive Prenatal Testing (NIPT) kits was valued at approximately USD 3.4 billion in 2023 and is anticipated to reach nearly USD 9.8 billion by 2032, showcasing a robust CAGR of 12.5% during the forecast period. This impressive growth is driven by several factors including advancements in diagnostic technology, increasing awareness among expectant parents, and the escalating incidences of chromosomal abnormalities.

One of the primary growth factors for the NIPT kit market is the rising prevalence of genetic disorders like Down syndrome, Edwards syndrome, and Patau syndrome among newborns. With an increasing number of older women opting for pregnancies, the risk of chromosomal abnormalities has surged, thereby driving the demand for non-invasive prenatal testing. Additionally, advancements in cell-free DNA technology have significantly improved the accuracy and reliability of these tests, further propelling market growth.

Another pivotal growth factor is the growing awareness and acceptance of non-invasive prenatal testing among healthcare providers and expectant parents. The non-invasive nature of these tests ensures that they pose minimal risk to both the mother and the fetus, making them a preferred option over invasive methods like amniocentesis. Furthermore, increasing educational campaigns and endorsements from healthcare organizations are enhancing the adoption rates of NIPT kits globally.

The market is also experiencing growth due to the continuous innovations and improvements in prenatal testing technologies. Companies are investing heavily in research and development to introduce advanced testing kits that offer quicker results, higher accuracy, and comprehensive genetic screening capabilities. This has led to the development of more sophisticated instruments and software that streamline the testing process and improve diagnostic outcomes.

Regionally, North America dominates the NIPT kit market due to its advanced healthcare infrastructure, high awareness levels, and supportive government policies. However, the Asia Pacific region is expected to exhibit the highest growth rate during the forecast period, driven by increasing healthcare expenditure, rising awareness, and the growing number of late maternal age pregnancies. Europe also holds a significant share, owing to advancements in healthcare technologies and increased acceptance of prenatal screening methods.

Product Type Analysis

In the NIPT kit market, the product type segment is classified into consumables, instruments, and software. Consumables, which include reagents, test kits, and other supplies used in the testing process, form a substantial part of the market. Due to the recurrent need for these items with each test conducted, consumables are expected to maintain a significant market share. The constant demand from laboratories and hospitals contributes significantly to the revenue generated in this segment.

Instruments used in NIPT, such as sequencers and analyzers, form another crucial segment. With continuous advancements in technology, newer and more efficient instruments are introduced, enhancing the accuracy and speed of prenatal tests. This segment, although requiring a higher initial investment, promises substantial growth due to the increasing adoption of advanced diagnostic tools in hospitals and diagnostic centers. The integration of AI and machine learning in these instruments further adds to their efficacy, making them indispensable in prenatal diagnostics.

Software solutions form the backbone of NIPT, as they are essential for analyzing the vast amounts of genetic data generated during testing. Robust software solutions enable precise interpretation of test results, ensuring accurate detection of genetic anomalies. Companies are focusing on developing advanced software that can handle complex genetic data and provide user-friendly interfaces for healthcare professionals. This segment is expected to grow significantly as software innovations continue to improve data analysis and reporting capabilities in prenatal testing.

Report Scope

Background. Whilst cannabis commercialization is occurring rapidly guided by highly individualistic public narratives, evidence that all congenital anomalies (CA) increase alongside cannabis use in Canada, a link with 21 CA’s in Hawaii, and rising CA’s in Colorado indicate that transgenerational effects can be significant and impact public health. It was therefore important to study Northern New South Wales (NNSW) a known cannabis use centre.

Methods. Design: Cohort. 2008-2015. Setting: NNSW and Queensland (QLD), Australia. Participants. Whole populations. Exposures. Tobacco, Risky Alcohol, Annual cannabis. Source: National Drug Strategy Household Surveys 2010, 2013. Main Outcomes. CA Rates. NNSW-QLD comparisons. Geospatial and causal regression.

Results. Cardiovascular, respiratory and gastrointestinal anomalies rose with falling tobacco and alcohol but rising cannabis use rates across Queensland. Maternal age NNSW-QLD was not different (2008-2015: 4,265/22,084 v. 96,473/490,514 >35 years, Chi.Sq.=1.687, P=0.194). A higher rate of NNSW cannabis-related than cannabis-unrelated defects occurred (prevalence ratio (PR)=2.13, 95%C.I. 1.80-2.52, P=3.24x10-19). CA’s rose more potently with rising cannabis than with rising tobacco or alcohol use. Exomphalos and gastroschisis had the highest NNSW:QLD PR (6.29(2.94-13.48) and 5.85(3.54-9.67)) and attributable fraction in the exposed (84.11%(65.95-92.58%) and 82.91%(71.75-89.66%), P=2.83x10-8 and P=5.62x10-15). In multivariable geospatial models cannabis was significantly linked with cardiovascular (atrial septal defect, ventricular septal defect, tetralogy of Fallot, patent ductus arteriosus), genetic (chromosomal defects, Downs syndrome), gastrointestinal (small intestinal atresia), body wall (gastroschisis, diaphragmatic hernia) and other (hypospadias) (AVTPCDSGDH) CA’s. In linear modelling cannabis use was significantly linked with anal stenosis, congenital hydrocephalus and Turner syndrome (ACT) and was significantly linked in borderline significant models (model P1.3 ranging up to 3.8x1030 making uncontrolled confounding unlikley.

Conclusions. These results suggest that population level CA’s react more strongly to small rises in cannabis use than tobacco or alcohol; cardiovascular, chromosomal, body wall and gastrointestinal CA’s rise significantly with small increases in cannabis use; and that cannabis is a bivariate correlate of AVTPCDSGDH and ACT anomalies and is robust to adjustment for other substances.

Purpose: We aim to determine the prevalence and characteristics of developmental disabilities among the clinical population of children who receive hearing health care in the United States.Method: Using electronic health records of 131,709 children (0–18 years), we identified those with a diagnosis of attention deficit/hyperactivity disorder, autism spectrum disorder, vision differences, cerebral palsy, chromosomal abnormalities, delayed milestones, Down syndrome, or intellectual disability. We determined prevalence, age of first audiology encounter, age of diagnosis for the developmental disability, and hearing status based on the specific disability and the number of diagnoses. Binomial and multinomial logistic regressions were performed.Results: One in four children had a diagnosed developmental disability. The most common disabilities were delayed milestones (11.3%), vision differences (7.4%), attention-deficit/hyperactivity disorder (6.6%), and autism spectrum disorder (6.2%). Half of the children with developmental disabilities had at least one diagnosis before their first audiology encounter. Children with developmental disabilities were more likely to have a reduced hearing or an unknown hearing status than children without developmental diagnoses. For children with reduced hearing, those with developmental disabilities had higher rates of bilateral configurations and poorer hearing severity levels.Conclusions: Developmental disabilities are common among children who seek hearing health care. Moreover, developmental disabilities often co-occur with reduced hearing. Further research and advocacy efforts are critical for creating clinical practices that are inclusive of, and equitable for, children with complex and diverse developmental profiles.Supplemental Material S1. ICD-9/10 umbrella mappings for the specific developmental disabilities used in the study.Supplemental Material S2. Binomial logistic regression results for if a diagnosis of attention deficit/hyperactivity disorder (ADHD) was known at the time of the first audiology encounter.Supplemental Material S3. Binomial logistic regression results for if a diagnosis of autism spectrum disorder was known at the time of the first audiology encounter.Supplemental Material S4. Binomial logistic regression results for if a diagnosis of cerebral palsy was known at the time of the first audiology encounter.Supplemental Material S5. Binomial logistic regression results for if a diagnosis of a chromosomal abnormality was known at the time of the first audiology encounter.Supplemental Material S6. Binomial logistic regression results for if a diagnosis of delayed milestones was known at the time of the first audiology encounter.Supplemental Material S7. Binomial logistic regression results for if a diagnosis of Down syndrome was known at the time of the first audiology encounter.Supplemental Material S8. Binomial logistic regression results for if a diagnosis of an intellectual disability was known at the time of the first audiology encounter.Supplemental Material S9. Binomial logistic regression results for if a diagnosis of a vision difference was known at the time of the first audiology encounter.Bonino, A. Y., Goodwich, S. F., & Mood, D. (2024). Prevalence and characteristics of developmental disabilities among children who receive hearing health care. American Journal of Audiology. Advanced online publication. https://doi.org/10.1044/2024_AJA-24-00118

This dataset provides Census 2022 estimates for long-term health conditions for all people by sex by age (in 6 categories) in Scotland.

Age

A person's age on Census Day, 20 March 2022. Infants aged under 1 year are classified as 0 years of age.

Sex

This is the sex recorded by the person completing the census. The options were "Female" and "Male". Guidance on answering the question can be found here

Long-term health condition (Source question or variables)

Individual question 18: Do you have any of the following which have lasted or are expected to last at least 12 months? (Tick all that apply)

• Deafness or partial hearing loss
• Blindness or partial sight loss
• Full or partial loss of voice or difficulty speaking (a condition that requires you to use equipment to speak)
• Learning disability (a condition that you have had since childhood that affects the way you learn, understand information and communicate)
• Learning difficulty (a specific learning condition that affects the way you learn and process information)
• Developmental disorder (a condition that you have had since childhood which affects motor, cognitive, social and emotional skills, and speech and language)
• Physical disability (a condition that substantially limits one or more basic physical activities such as walking, climbing stairs, lifting or carrying)
• Mental health condition (a condition that affects your emotional, physical and mental wellbeing)
• Long-term illness, disease or condition (a condition, not listed above, that you may have for life, which may be managed with treatment or medication)
• Other condition, please write in:
• No condition

Long-term health condition: nature of condition

This variable indicates whether or not an individual has identified themselves as having a long term health condition which has lasted or is expected to last at least 12 months. The conditions presented as response options were deafness or partial hearing loss, blindness or partial sight loss, a learning disability (for example Down’s Syndrome), a learning difficulty (for example dyslexia), a developmental disorder (for example autistic spectrum disorder or Asperger’s syndrome), a physical disability, a mental health condition, a long-term illness, disease or condition and other condition. (Although the categories ‘Long-term illness, disease or condition’ and ‘Other condition’ were presented as separate response options, they were combined into a composite ‘Other condition’ category for the purposes of statistical outputs.)

The classification is shown here

Long term health condition: Blindness or partial sight loss

An indicator for whether a person is blind or partially vision impaired.

Long term health condition: Deafness or partial hearing loss

An indicator for whether a person is deaf or partially hearing impaired.

Long-term health condition indicator - Long-term Illness

An indicator for whether a person has a long term illness (a condition, not listed in the other tick box response options for the long term health conditions question, that a person may have for life, which may be managed with treatment or medication)

Long-term health condition indicator - Mental Health

An indicator for whether a person has a mental health condition (a condition that affects emotional, physical and mental wellbeing)

Long-term health condition indicator - Physical Disability

An indicator for whether a person has a physical disability (a condition that substantially limits one or more basic physical activities such as walking, climbing stairs, lifting or carrying)

Long-term health condition indicator – Speaking difficulty (full or partial voice loss)

An indicator for whether a person has a speaking difficulty (a condition that requires a person to use equipment to speak).

The quality assurance report can be found here

Objective: To determine if elevated rates of autoimmune disease are present in children with both Down syndrome and moyamoya disease given the high rates of autoimmune disease reported in both conditions and unknown etiology of angiopathy in this population.Methods: A multi-center retrospective case-control study of children with Down syndrome and moyamoya syndrome, idiopathic moyamoya disease, and Down syndrome without cerebrovascular disease was performed. Outcome measures included presence of autoimmune disease, presence of autoantibodies and angiopathy severity data. Comparisons across groups was performed using the Kruskal-Wallis, χ2 and multivariate Poisson regression.Results: The prevalence of autoimmune disease were 57.7, 20.3, and 35.3% in persons with Down syndrome and moyamoya syndrome, idiopathic moyamoya disease, and Down syndrome only groups, respectively (p < 0.001). The prevalence of autoimmune disease among children with Down syndrome and moyamoya syndrome is 3.2 times (p < 0.001, 95% CI: 1.82–5.58) higher than the idiopathic moyamoya group and 1.5 times (p = 0.002, 95% CI: 1.17–1.99) higher than the Down syndrome only group when adjusting for age and sex. The most common autoimmune diseases were thyroid disorders, type I diabetes and Celiac disease. No individuals with idiopathic moyamoya disease had more than one type of autoimmune disorder while 15.4% of individuals with Down syndrome and moyamoya syndrome and 4.8% of individuals with Down syndrome only had >1 disorder (p = 0.05, 95%CI: 1.08–6.08).Interpretation: This study reports elevated rates of autoimmune disease in persons with Down syndrome and moyamoya syndrome providing a nidus for study of the role of autoimmunity in angiopathy in this population.

In 2022, it was estimated that 5.1 percent of those aged 21 to 64 years had a cognitive disability, such as Down syndrome, autism, or dementia. This statistic presents the percentage of people in the U.S. with a cognitive disability as of 2022, by age.

The aim of this publication is to provide information about the key differences in healthcare between people with a learning disability and those without. It contains aggregated data on key health issues for people who are recorded by their GP as having a learning disability, and comparative data about a control group who are not recorded by their GP as having a learning disability. Six new indicators were introduced in the 2022-23 reporting year for patients with and without a recorded learning disability. These relate to: • Patients with an eating disorder • Patients with both an eating disorder and autism diagnosis • Patients with a diagnosis of autism who are currently treated with antidepressants More information on these changes can be found in the Data Quality section of this publication. Data has been collected from participating practices using EMIS and Cegedim Healthcare Systems GP systems.

BackgroundVojta therapy (VT) enhances postural control and improves gait abilities. However, there is limited evidence regarding the impact of home-based VT on individuals with Down syndrome (DS).ObjectiveThis study aimed to assess the feasibility and preliminary effects of a two-week home-based VT program on spatiotemporal gait parameters in individuals with DS.MethodsSixteen individuals with DS (mean age = 17.88 ± 4.57 years, 8 females) participated in a two-week home-based VT program. Feasibility was measured through adherence rates and the occurrence of adverse events. Spatiotemporal gait parameters were evaluated before and after the intervention using the Vicon motion capture system.ResultsAll participants (100%) successfully completed the home-based VT program with no reported adverse events. Significant improvements were observed in walking speed, cadence, step time (left and right), stride time (left and right), step length (left and right), stride length (left and right), and single support (left and right) (p