Determinants of Healthcare Costs in Individuals With Down Syndrome: A Systematic Review

ABSTRACT

Background

Individuals with Down syndrome (DS) require specialized medical follow‐up and services more frequently than the general population, resulting in substantial healthcare costs for families and health systems. This systematic review aimed to synthesize evidence on the magnitude and determinants of direct healthcare and indirect costs associated with DS.

Methods

We searched Web of Science, PubMed, and Scopus for observational and experimental studies published in English between January 1, 2000, and December 31, 2022 (updated June 15, 2024), that reported healthcare costs or cost determinants for individuals with DS. Reference lists were also screened. We excluded non‐English papers, qualitative studies, reviews, protocols, editorials, and gray literature.

Results

The search identified 625 unique citations, of which 14 matched the inclusion criteria. Half were conducted in the USA. Inpatient services constituted the largest share of direct healthcare costs in 58% of studies. Indirect costs, mainly productivity losses among families, were reported in 25% of studies. Healthcare costs were highest during infancy (driven primarily by congenital heart defects and early hospitalizations), decreased throughout childhood and adolescence, and increased again in adulthood, particularly after age 40, due to age‐related comorbidities such as dementia and multimorbidity. Associated morbidities, greater functional limitations, and lower socioeconomic status were consistently associated with higher costs.

Conclusions

Age, comorbidities, functional ability, and socioeconomic factors are key drivers of healthcare costs in DS. Long‐term, comprehensive policies integrating medical, social, and educational support are needed. Priority should be given to early cardiac surgery coverage, multidisciplinary adult transition clinics, subsidized respite care, and financial assistance schemes to reduce both inpatient utilization and family productivity losses.

Abbreviations

DS

Down syndrome

PICOS

Patient, Intervention, Comparator, Outcome, and Study design (PICOS)

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta‐Analyses

USA

United State of America

1. Introduction

Down syndrome (DS) is a chromosomal disorder associated with substantial medical and social costs, caused by the presence of all or a portion of a third chromosome 21. It is the most common genetic disorder worldwide and an important genetic cause of intellectual disabilities, occurring in approximately 1 in 400–1500 newborns [1, 2]. DS can include a range of medical conditions, such as learning disability, epilepsy, mental health difficulties, emotional problems, sleep disorders, hypotonia, blood disorders, and so forth, which may be distinguished at birth or develop during the life span [3].

Significant advancements in medical and surgical care, especially of early‐stage comorbidities, have resulted in increased newborn, child [4], and adult survival [5]. As a result, there may be greater demand for health services and higher costs for individuals with DS and their families.

Individuals with Down syndrome require individualized healthcare, regular follow‐up, psychosocial support, rehabilitation services, and special education, which impose substantial direct healthcare expenditures on families and health systems. Evidence indicates that mean and median healthcare expenditures for children with Down syndrome are 12–13 times higher than for children without Down syndrome and show relatively little variation by age in early childhood [6, 7]. Similarly, out‐of‐pocket medical expenses remain significantly elevated, with families of children with Down syndrome facing considerably higher annual costs compared to families of typically developing children [8].

In comparison with typically developing children of the same age, children with intellectual disabilities, including those with Down syndrome, require more frequent therapy sessions and greater caregiving time [9]. This substantial time commitment reduces caregivers' leisure time and work capacity, leading to high emotional and financial costs for families and society as a whole [10]. Recent Australian research estimated that the average cost of caring for adults with moderate to severe intellectual disabilities over a 6‐month period amounted to US$48,087–$58,129 for families, largely driven by lost productivity and additional caregiving demands [11].

Beyond the burden on families, Down syndrome also imposes a considerable economic burden on society. Waitzman et al. estimated that in the United States, approximately 4100 newborns with Down syndrome are born each year, with the lifetime economic burden per new case reaching US$451,000 (in 1992 dollars), resulting in a total annual societal burden of about $1.8 billion for all new cases [12]. A preliminary study in China further highlighted that the lifetime economic burden of a new Down syndrome case was approximately US$47,000 from the family perspective and US$55,000 from the societal perspective, with indirect costs (mainly productivity losses) accounting for the largest share [13].

Despite growing evidence of these substantial direct and indirect costs associated with Down syndrome, no systematic review has comprehensively synthesized the global evidence on the determinants of these lifetime healthcare and societal costs. The present review addresses this important knowledge gap.

Some characteristics, such as age, functional ability, and associated comorbidities, might exacerbate the financial burden of DS. Intellectual disability, congenital heart disease, ophthalmological problems, decreased thyroid function, unusual flexibility and degenerative changes in many joints, and obesity are some of the problems that affect patients with DS [6, 14], resulting in high medical costs [7]. Adults with DS are also at an increased risk of developing Alzheimer's disease (AD). The median age at death for persons with Down syndrome has risen substantially in recent decades, from 25 years in 1983 to approximately 55–60 years in more recent data [9, 10], resulting in a significant rise in the number of people with DS living with age‐related chronic diseases, such as dementia [8, 11, 15]. Because of the problems associated with DS, and life‐long care, non‐medical services, such as supportive care and special education, may also be necessary [13].

The effects of DS on people and their families may impact work, family connections, living standards, social interactions, personal functioning, and quality of life. These costs may vary by age, geographical location, extent of co‐morbidities, severity of intellectual disabilities, and so forth. Greater understanding of the factors that influence costs, can help identify areas of need that could be targeted in order to reduce the burden of DS, including development and delivery of cost‐effective treatment alternatives and support systems. This systematic review aimed to determine the healthcare costs of DS to families and healthcare systems across the globe, as well as any non‐medical and indirect costs, such as productivity losses, and to identify factors associated with these costs.

2. Methods

2.1. Search Strategy

This systematic review adheres to the PRISMA principles. Searches were conducted by SS on Web of Science, PubMed, and Scopus to include English language articles from January 1, 2000, onward. We chose January 1, 2000, as the lower limit because major improvements in survival and medical management of Down syndrome occurred from the late 1990s onward, substantially changing cost patterns. To ensure contemporary relevance, we updated the searches in all three databases on June 15, 2024, and again on January 2, 2026 (no new eligible studies were identified in either update).

The databases were searched using a combination of MeSH terms and keywords, including “Down syndrome,” “economic burden,” “financial burden,” “catastrophic expenditure,” “productivity loss,” “indirect cost,” “out‐of‐pocket,” “expenditure,” “cost,” and “spending.” Boolean operators were used to combine subject headings and relevant search terms related to Down syndrome and healthcare‐related costs (e.g., “Down syndrome” AND (“health expenditure” OR “economic burden” OR “cost” OR “indirect cost”)). The search strategies are outlined in Table 1. Authors kept the search terms broad to enable more studies to be screened.

TABLE 1.

Search strategy in the included databases.

Databases	Number of abstracts
Web of Science ISI‐(TI = (cost* OR expend* OR spend* OR econom* OR financ*) AND AB = (syndrom* AND down*)) AND LANGUAGE: (English) AND DOCUMENT TYPES: (Article)	142
PubMed PUBMED‐ (cost*[Title] OR expend*[Title] OR spend*[Title] OR econom*[Title] OR financ*[Title]) AND (syndrom* [Abstract] AND down* [Abstract])	260
Scopus Scopus‐TITLE (cost* OR spend* OR expend* OR econom* OR financ*) AND TITLE‐ABS (syndrom* AND down*)	223

In addition to database searches, the reference lists of all included studies and relevant review articles were manually screened to identify any additional eligible publications. Furthermore, forward citation tracking was conducted using Google Scholar to identify studies that cited the included articles. This supplementary search process was performed independently by two reviewers, and any potentially relevant records were assessed against the predefined inclusion criteria. One additional study was identified through reference list screening and included in the final review.

Search results were exported into EndNote, and duplicates were removed. After removing duplicate records, two reviewers (STR and MRM) independently screened the titles and abstracts for relevance and subsequently assessed and selected relevant full‐text articles. When the study title and abstract potentially met the inclusion criteria, the complete paper was retrieved and reviewed. Agreement between the two independent reviewers for full‐text inclusion was excellent (Cohen's κ = 0.92). All disagreements were resolved by consensus with a third senior reviewer (SS). The corresponding author (SS) confirmed the eligibility of included studies.

2.2. Inclusion and Exclusion Criteria

Studies were eligible if they were published in English from January 1, 2000, onward, if they were observational (cross‐sectional studies, case‐control studies, and cohort studies) or experimental (randomized controlled trial and quasi‐experimental) studies reporting healthcare costs for individuals with Down syndrome (DS) or factors associated with these costs.

Papers were excluded if they were: qualitative, case studies, abstracts, editorials, letters to the editor, or comments; protocols or methods papers; gray literature (e.g., books, conference abstracts, theses, research reports, and policy documents); or non‐English language publications. The inclusion criteria based on the PICOS framework are summarized in Table 2.

TABLE 2.

PICOS inclusion criteria.

PICOS	Criteria
Population	Individuals with DS
Intervention	Healthcare services (inpatient visits, outpatient visits, therapies, medicines, etc.)
Comparator	N/A
Outcome	Cost determinants
Study design	Observational and experimental studies

2.3. Data Extraction and Analysis

We extracted the following data: author, year, country, sample size, age, sex, study design, healthcare services/interventions (inpatient visits, outpatient visits, therapies, medicines, etc.), costs included, and factors associated with cost. Three main steps of title, abstract, and full‐text screening were performed to select the included studies. Data were extracted from all included studies using a pre‐specified checklist of essential study items. The corresponding author checked the accuracy of the data by comparing and cross‐checking the extracted data with the information contained in the included articles. All disagreements were resolved by consensus after discussion. We used EndNote X9.3 to screen the papers and extract data.

2.4. Quality Assessment

Because the Bassi and Lau framework is designed for economic evaluations rather than cost‐of‐illness studies, we replaced it with the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Economic Evaluations combined with selected items from the IHE Cost‐of‐Illness Study Quality Appraisal Checklist. Overall quality of included studies ranged from moderate to high; no study was excluded on the basis of quality.

It should be noted that in all papers, the dollar refers to the US dollar in 2019.

3. Results

3.1. Study Characteristics

Search of the three databases yielded 625 studies. Five hundred fifty articles were excluded in the first screening phase (title screening) due to language, date of publication, or duplicates. Fifty‐five papers were excluded in the second phase of screening (abstract screening) due to study design (qualitative studies or an excluded design), participants (not persons with DS), article type (letter to the editor, editorial, and review), or no focus on healthcare costs. The complete text of the remaining 20 publications was examined in the last phase (full‐text screening), and seven more studies were excluded having no focus on healthcare costs. Reference lists of all 13 articles were screened, and one additional article was found to meet inclusion criteria and was included in the review. As a result, 14 articles fulfilled the inclusion requirements. The study selection process is shown in Figure 1.

FIGURE 1.

Flow diagram of study selection.

Table 3 shows a summary of the characteristics of included studies. Of the 14 studies identified, seven (50%) were carried out in the USA of America (USA), two in Canada, one in Mexico, one in Taiwan, one in China, one in Australia, and one in South Korea.

TABLE 3.

Study characteristics.

Authors (year)	Country	Study sample size (age)	Study design	Study perspective	Indirect cost adjusted inflation to 2019 USD	Inpatient cost adjusted inflation to 2019 USD	Rehabilitation cost adjusted inflation to 2019 USD	Medicine cost adjusted inflation to 2019 USD	Outpatient cost adjusted inflation to 2019 USD	Total cost adjusted inflation to 2019 USD
Bayen et al. (2020)	USA	878 (age > 45)	Case study, economic evaluation	Healthcare payers (medicare)	NA	DS with dementia:$23,699 DS without dementia: $16,389	NA	NA	DS with dementia:$489 DS without dementia: $528	Direct costs: DS with dementia: $34,626 DS without dementia: $24,132
Martı´nez et al. (2019)	Mexico	50 (age > 18)	Cross‐sectional analysis	Patient (household with this child)	Transportation:107$	NA	NA	NA	NA	OOP: $464
Kageleiry et al. (2016)	USA	5167 (all ages)	Retrospective matched‐cohort study	Healthcare system	NA	OOP: age < 1: 751 age 1 to < 3: 848 age 3 to < 5: 706 age 5 to < 595 age 13 to < 18: 354	NA	OOP: age < 1: $159 age 1 to < 3: $214 age 3 to < 5: $179 age 5 to < 13: $197 age 13 to < 18: $214	OOP: age < 1: 1260 age 1–3: 511 age 3–5: 439 age 5–13: 293 age 13–18: 199	OOP: age 0 to < 1: 2669 age 1 to < 3: 2158 age 3 to < 5: 1624 age 5 to < 13: 1307 age 13 to < 18: 895
Boulet et al. (2008)	USA	420 (age 0–4)	Case study	Healthcare payers: insurance	NA	$25,936	NA	$1101	$16,142 (physical, speech, and occupational therapy were included)	Medical cost:$43,204
Chen et al. (2008)	China	222 (all ages)	Case study	Patient (household with this child)	Productivity loss to the family: $8789 productivity loss to the person with DS:$54,648	Age 0–6: $489 other ages: NA	$574	NA	age 0–6:$171 age 7–18:$293 age > 19:$147	Direct healthcare cost$: 205 Direct non‐health cost:$ 21
Dawson et al. (2014)	USA, Florida	2715 (age 0–10)	Retrospective Population‐based study	Healthcare system	NA	Median cost: age 1: 7698 age 2: 6628 age 3–4: 5659 age 5–6: 5082 age 7–8: 8003 (small sample with most likely comorbid condition)	NA	NA	NA	NA
Geelhoed et al. (2011)	Australia	363 (age < 25)	Population‐based study	Patient (household with this child)	NA	Hospital care: mean:1703 median:42	Mean:2625 median:144	Mean:144 median:28	GP and specialist: mean:646 median:506	Mean direct cost: 5119 median direct cost:$ 2069
Derrington et al. (2013)	USA	504 (age: 0–3)	Population‐based study	Public health	NA	NA	NA	NA	NA	Mean:22,814 median: 9426
Genereaux et al. (2016)	Canada	51 (preschool and school age)	Population‐based retrospective survey	Patient	(It is not only for healthcare) transportation:389 * Employment Income loss due to reduced work hours: For preschool child: $6769 For school‐age child $16,144	NA	NA	NA	NA	Parental cost of raising a DS children:(median) preschool: $29,983 school age:$ 36,707 Annual societal cost of raising DS children:(median) preschool:$7248 school age: $33,138
Hung et al. (2011)	Taiwan	375 (all ages)	Population‐based retrospective survey	Healthcare payers and hospital	NA	5427	NA	Medicine and pharmacy service fee in hospital: 611	NA	NA
Park et al. (2019)	South Korea	2153 (under 9)	Cohort study, nationwide population‐based study	Healthcare system and insurer	NA	NA	NA	NA	NA	Age 0 (2019): 19,908 age 9 (2019): 1673 USD
Mendiratta et al. (2018)	USA	> 65	Retrospective Population‐Based Study	Healthcare payers include patients (hospital bill)	NA	NA	NA	NA	NA	Mean: 18,572 SD:5712
Uma Athale (2022)	Canada	711 patients (under 18) Cost data was available for 533 patients	Cohort population‐based study	Healthcare system	NA	Median 5‐year 98,424	NA	NA	NA	Median 5‐year cost of acute lymphoblastic leukemia was: 190,915 among DS patients
Eleonore Bayen (2021)	USA	353 (45–89)	Population‐based (cross‐sectional study)	Healthcare system	NA	With dementia: 25,809 Without dementia: 17,848	NA	NA	With dementia: 532 Without dementia: 575	With dementia: 37,708 Without dementia: 26,281

3.2. Direct Healthcare Costs

We collected data from included studies on costs paid by individuals, health insurers, and national health systems in the included studies. The costs that were included in the reviewed studies varied. Some research included both healthcare costs and indirect costs, while others included just limited aspects of direct healthcare costs like rehabilitation, pharmacy, or therapy. A number of studies showed that inpatient charges accounted for the largest proportion of the overall healthcare spending for individuals with DS. In the USA, Kageleiry et al. (2016) divided expenditures into hospital, outpatient, emergency, home healthcare, pharmacy, and other medical costs (e.g., laboratory/pathology costs). They demonstrated that during the first year of life, inpatient costs are high, but outpatient costs become more significant as the child grows [8].

In another study conducted in Australia, Geelhoed et al. (2011) classified therapy and respite costs into a category of “other medical costs.” They indicated that while therapies, such as physiotherapy, occupational therapy, hydrotherapy, and speech therapy dominated in the younger age groups, respite care was the highest cost for the older age groups. Therapy accounted for 85% of “other medical costs” for ages 0–4 years, but only 35% for ages > 20. In the same age categories, respite care expenditures jumped from 4% to 60% of “other medical costs,” respectively. Including rehabilitation costs, yearly mean direct healthcare costs were $5119 (adjusted for the 2019 inflation rate), with a median cost of $2069 [12].

Seven research studies (58.33% of total included studies) showed that inpatient services, hospital care equipment, and emergency department services accounted for a higher share of total health costs than outpatient services. For example, in the USA, Derrington et al. (2013) reported that the median cost of hospitalization per child was $15,811, which was about 13 times more than the median cost for children without DS. In addition, the study reported that the overall cost of hospitalization for 504 children with DS from 1999 to 2007 was approximately $20.2 million in 2011, with prenatal and postnatal hospitalization costing $10.5 million and $9.7 million, respectively. Moreover, 52.7% of hospitalization expenses in the year post‐birth occurred before the child was 6 months of age. The mean incremental cost for children with DS vs. those without was $17,365 at birth. Average hospital costs for children with DS were $40,075 in the same period, which was 9 times greater than the average cost for children without DS [16].

Inpatient costs were found to decrease with increasing age, which is consistent with the fact that older individuals with DS have fewer medical difficulties that require hospitalization. In the USA, Boulet et al. (2008) found that there were more hospitalizations in children aged 1 year. The average healthcare costs for children with DS were consistently higher than those without DS. For example, inpatient expenditures were 15 times greater for newborns with DS compared with newborns without DS, and 75% of DS infants had at least one admission compared to 16% of non‐DS newborns. Infants with DS had the highest average yearly inpatient charges ($68,307), while children aged 3–4 had the lowest out of children 0–4 with DS ($2123) [7].

Outpatient and community‐based services, such as physician visits, emergency room visits, home health agency consumption, and in some studies, pharmacy costs, were not significantly different between different age groups with DS. Kageleiry (2016) found that despite the extra co‐payments associated with multidisciplinary outpatient visits for individuals with DS, these expenditures were still higher for individuals with DS than the control group without DS in the USA [17]. As a result, in countries where such services are paid for out of pocket, there would be a considerable financial burden on DS families. For children aged 1–2 and 3–4 years with DS, average outpatient costs were roughly 10 and 12 times higher than children of the same age without DS in the USA, according to Boulet et al. (2008) [7].

Patients with DS also had greater mean annual out‐of‐pocket medical expenses than non‐DS patients. Inpatient expenditures in the first year of birth ($925) and outpatient costs ranging from $183 to $623 were the primary drivers of out‐of‐pocket costs associated with DS. Individuals with DS had lower and equivalent incremental out‐of‐pocket costs for pharmacy and emergency room visits. Between birth and 18, individuals with DS experienced $18,248 in additional out‐of‐pocket medical expenditures compared with those without DS. When expenditures are amortized over 18 years, families of children with DS pay an extra $84 each month for out‐of‐pocket medical costs in USA [17].

Similarly, Park et al. (2019) in South Korea noted that children with DS are typically born with several congenital defects, which are associated with significant medical and out‐of‐pocket expenditure in Korea. Out‐of‐pocket expenditures for non‐DS children peaked at the age of 1‐year‐old, whereas they peaked during infancy and decreased steadily as they grew older for DS children. Congenital defects in children with DS were associated with substantial medical and out‐of‐pocket expenditures. Also, they indicated that out‐of‐pocket medical expenditures for DS children were around twice as expensive as for non‐DS children [18]. In another study, Martinez et al. (2019) in Mexico found that out‐of‐pocket medical expenditures were high for all age groups. Annual out‐of‐pocket expenses for a child with DS accounted for, on average, 27% of the available household spending. Furthermore, one‐third of the families (33%) experienced catastrophic costs, and 46% had to borrow money from relatives to pay for medical treatment. These percentages represent the risk of impoverishment encountered by families with DS children [19].

3.3. Indirect Costs

Three studies (25% of total included studies) reported productivity losses for people with DS and their families. Early mortality and morbidity, economic losses for persons with DS due to limited labor force participation and premature death, and economic losses for families due to lower productivity, all contributed to these indirect costs. This study indicates that the average lifetime economic burden of a new DS case, from the family's standpoint, was $47,000, and from the perspective of society, it was $55,000. The productivity loss experienced by people with DS accounted for 75%–84% of the entire economic burden, and the productivity loss experienced by families accounted for 13%–23% of the total economic burden [13].

Martinez et al. (2019) in Mexico, on the other hand, gathered information on family income and overall expenditures, including transportation costs and medical care‐related expenses for children with DS, as well as hours spent caring for these children. Their findings indicated that the average daily care time was 11.22 h or 78.5 h per week, but the study also revealed that time spent on care increases with the age of the child with DS, suggesting that the negative impact on productivity increases over time [19].

A study by Genereaux et al. (2016) in Canada showed that the severity of an intellectual disability has a detrimental impact on job and professional advancement. Fifteen of the 17 participants who were working mothers claimed their capacity to work had been impacted; 24 of the 29 mothers and six of the 23 fathers cited that their job and career advancement had been negatively affected by caring responsibilities [20].

Another indirect cost of DS identified by studies included in this review was the education of DS children. Median annual total expenditure reported for preschool [21] and school‐age parental costs were $29,983 and $36,707 (adjusted for inflation to 2019 USD), respectively [20].

3.4. Key Determinants of Healthcare Cost Among Individuals With DS

Table 4 summarizes the major contributing factors to healthcare costs among individuals with DS, and the direction of the relationship, as reported by included studies.

TABLE 4.

Key determinants of healthcare costs among individuals with Down syndrome (DS).

Determinant	Direction of association	Number of studies	Consistency	Representative references
Associated comorbidity	+ (higher cost)	7	High	Bayen 2020, Hung 2011, Boulet 2008, Dawson 2014, …
Functional disability/dependence	+ (higher cost)	1	Moderate	Geelhoed 2011
Age	Mixed (↑ infancy, ↓ childhood, ↑ older adulthood)	5	Moderate–high	Boulet 2008, Kageleiry 2016, Park 2019, Martínez 2019, Geelhoed 2011
Lower socioeconomic status	+ (higher cost/burden)	2	Moderate	Martínez 2019, Chen 2008
Ethnicity (e.g., Hispanic and Black)	Mixed/context‐dependent	2	Low–moderate	Bayen 2020, Derrington 2013
Urban vs. rural location	+ in urban	1	Limited evidence	Bayen 2020

3.5. Associated Morbidity

In several of the included studies, related morbidities constituted a major contribution to overall healthcare costs in people with DS. For example, in research carried out in the USA, Bayen et al. (2020) reported that DS persons with dementia had higher healthcare costs than DS adults without dementia. DS dementia was associated with a significantly higher level of multimorbidity, more emergency room visits (88%), and more primary care physician visits (91.2%) [21]. Surprisingly, in other research, the opposite was found for DS with Alzheimer's disease; mean cost of hospitalization for patients with both DS and Alzheimer's disease was $15,972.6 per hospitalization, compared to $18,621.85 for people with DS without AD [22].

Evidence from the USA also suggests that costs for children with DS were greater if they had co‐morbid coronary heart diseases (CHDs); this difference was particularly noticeable among infants. For infants with DS and CHDs, mean and median costs were 5–7 times higher than for infants with DS who did not have CHDs. For children aged 1–4 years, mean and median costs were generally about twice as high for children with DS and CHDs as for children with DS who did not have CHDs [7]. In another study, also carried out in the USA, Dawson et al. (2014) found that mean estimated inpatient costs for infants with DS and severe CHDs were approximately 11 times those for infants with isolated DS during the first year of life; median costs for infants with severe CHDs were more than 26 times those for infants with isolated DS [23].

3.6. Limitations in Functional Abilities

According to included studies, greater functional impairment was linked to higher costs. According to Geelhoed et al. (2011), in Australia, functional independence increasing on the WeeFIM scale was related to a considerable reduction in overall cost, a moderate reduction in hospital and other expenditures, and minor reductions in medical and pharmacy costs adjusted for age. Even after adjusting for age, the most dependent individuals had the highest total expenditures, including higher hospital, medical, and other costs [12].

3.7. Age

A key finding is the non‐linear (U‐shaped) relationship between age and direct healthcare costs: costs peak in infancy due to surgical interventions (mainly for congenital heart defects) and frequent hospitalizations, decrease markedly during childhood and adolescence as acute events become less common, and rise again in adulthood (particularly after age 40) due to accelerated aging and age‐related comorbidities, such as Alzheimer‐type dementia, hypothyroidism, obstructive sleep apnea, obesity, osteopenia/osteoporosis, and multimorbidity. This pattern is consistent across studies but varies by healthcare system (e.g., higher inpatient costs in private insurance models like the USA compared to single‐payer systems) [7].

According to some research, direct expenditures are greatest in the first year and drop as one ages. Martinez et al. (2019) in Mexico found that 75% of infants with DS had at least one hospital admission compared to 16% of infants without DS [7]. A household with children aged 5 or older had a higher proportion of catastrophic spending than a household with younger children [19]. According to Dawson's study (2014), in the USA, for all children with DS, the median predicted inpatient expenditures decreased until age 6 [23]. Therefore, direct costs were reduced as individuals became older [12]. The decline in expenditures was due to decreased hospital, medical, and treatment costs as people aged. Conversely, indirect costs rise due to respite care, comorbidities, and dependency which increase with age [12].

3.8. Socioeconomic Characteristics

Included studies showed that the prevalence of DS was greater in families with a lower socioeconomic status (SES) than in those with a higher SES. The value of productivity, such as GDP per capita or salary, as well as the productivity of individuals with DS, were also shown to be influencing variables in the economic burden of DS [13]. In their study in Mexico, Martinez et al. (2019) indicated that 67% of families with DS who received medical care in Mexico were in the bottom four deciles of income, indicating a restricted ability to pay for medical services. According to this survey, 33% of families with DS children faced catastrophic expenditures, and 46% of those households had to borrow money to cover medical costs. The average out‐of‐pocket expenses accounted for almost 27% of total available household income (equal to $464): 21% for out‐of‐pocket medical care, and 6% for transportation costs [19].

In terms of geographical variations, one study, carried out in the US, found that the costs of DS were higher in urban regions than rural areas, with evidence to suggest that higher costs were related to larger urban hospitals and the authors suggest that there may be greater unmet needs for DS individuals living in rural areas [21].

Race/ethnicity was another social component that independently impacted costs. Derrington et al. (2013) found that Hispanic children with DS had a 60% higher risk of post‐birth hospitalization in the USA. Children born to Hispanic vs. non‐Hispanic White mothers had the highest disparities in postnatal hospitalizations and days spent in the hospital. Although there were fewer hospitalizations for children with DS born to non‐Hispanic black mothers, they spent more extended time in the hospital than children with DS born to non‐Hispanic white mothers [16].

Similarly, Bayen et al. (2020), in a study carried out in USA, indicated that African American and Hispanic ethnic groups tend to rely more on informal caregivers and have less access to residential care facilities and other support systems, resulting in more expensive hospital stays due to late intervention among DS children from these ethnic groups. They stated that blacks had the greatest average annual per capita Medicare expenditures, followed by Asians, North American natives, Hispanics, and whites with the lowest levels of expenditure [21].

4. Discussion

To develop up‐to‐date evidence regarding healthcare and other costs and drivers of these costs among people with DS, we reviewed literature published between 2000 and 2022. Only 14 studies were identified that addressed the review questions. Although most articles on DS‐related costs originated in the USA, studies were also identified from Canada, Taiwan, China, Australia, and South Korea, providing a broader scope.

This systematic review reveals that both direct and indirect healthcare costs represent significant economic burdens for individuals with DS and their families. Direct costs encompass medical expenses, such as hospital visits, treatments, and medications, while indirect costs include lost productivity and additional care‐related expenses. The reviewed studies consistently indicate that factors, such as age, associated morbidities, functional impairments, and socioeconomic status significantly influence these costs. For instance, older individuals and those with severe comorbidity conditions tend to incur higher medical expenses due to increased healthcare needs and more frequent hospitalizations [24, 25].

A critical interpretation of these findings is the necessity for tailored healthcare policies that address both direct and indirect costs. Effective care coordination and support mechanisms are essential to alleviate the financial strain on families. For example, integrating comprehensive healthcare and insurance strategies can improve access to necessary medical services, thereby reducing out‐of‐pocket expenses for families. Additionally, community support programs can help mitigate the indirect costs by providing respite care and other support services, enabling family members to maintain employment and reduce income loss [26, 27].

In Taiwan, individuals with DS had longer inpatient days (and higher medical expenses) as a result of their age when compared to the general population [28]. Some of the studies showed that children with DS require particular healthcare services more than others due to a higher risk of chronic disease, and adverse physical, developmental, behavioral, or emotional health issues [29, 30]. Furthermore, studies revealed that people with DS had a faster aging physiology, implying a greater demand for more proactive and responsive treatment to decrease emergency‐related care in these vulnerable people [31, 32]. These conditions necessitate regular medical and social care, which can result in increased healthcare costs for individuals, their families, and the health system.

Four major factors were reported by included studies to influence the cost of DS healthcare, including associated morbidity, functional disability, age, and socioeconomic characteristics (including socioeconomic status, urban vs. rural, and ethnicity). In general, costs were shown to be higher for people with comorbid conditions (such as CHD and dementia), for people with poorer functional disability, for people with lower socioeconomic status and for people living in urban vs. rural areas. The relationship with costs was less clear for age and ethnicity.

4.1. Associated Morbidity

In terms of co‐morbidity, the majority of included studies that reported cost of comorbidities found that costs were higher for people with comorbid conditions compared to those without the comorbid conditions. According to Startin et al. (2020), the prevalence of multiple comorbidities differs across lifetimes in individuals with DS, and these comorbidities are associated with an increase in healthcare utilization and hospitalizations [33]. In another study, Urbano and Hodapp (2007) in the US discovered that children with DS are more likely to be admitted to the hospital at early ages, especially if they suffer from respiratory diseases or congenital heart problems that require special care [34]. According to the majority of research, roughly 46%–56% of all newborns with DS have a medical diagnosis of a CHD [24, 25, 26, 34]. While the majority of research, such as those conducted by Hung et al. (2011) in Taiwan, indicates that DS with severe disease is more likely to require hospitalization, have more extended hospital stays, and have higher healthcare costs than their peers [28], Dobson and Middleton (1998), in the UK found that costs were not statistically different between DS children with and without associated comorbidities. This finding may reflect a lack of power due to the small sample size [27].

4.2. Limitation in Functional Abilities

In terms of functional disability, several included studies showed a relationship between greater functional impairment and higher costs. In the USA, Chapman et al.(1991) assessed children with and without DS in terms of cognitive, motor, language, and socio‐emotional development; children with DS, demonstrated lower performance than children in the control group [35]. As shown by Wu et al. in their study, there is a significant financial burden on families due to various physical issues that DS children have, which require costly health services [36]. Furthermore, with regard to their functional impairments, individuals with DS may be less productive than individuals without DS, which is further factor indirectly impacting the cost of DS. All in all, overall costs increased as dependency increased in all age groups. Indirect costs, which can include early mortality and morbidity, economic losses for people with DS due to reduced labor force participation and premature death, and economic losses for families due to reduced productivity, were found to constitute the majority of the economic burden of DS in the studies reviewed.

4.3. Age

The association between age and healthcare costs among patients with DS was not straightforward in the included study. According to a number of studies, DS morbidity rates are highest in infancy and early childhood in comparison to older children and adolescents [37], with increased risk, for example, of heart abnormalities [38] or gastrointestinal issues (such as tracheoesophageal fistula, duodenal blockage, Hirschsprung disease, and imperforate anus [39]), requiring medical or surgical intervention. As a result, direct costs are typically highest in the first year of childhood and gradually decrease as one continues to age [38] but there are many other items that affect the health cost by aging. The fact that children with DS have medical concerns that require hospitalization is consistent with the fact that roughly 40%–50% of newborns with DS are recognized as having heart abnormalities, many of whom will require surgical treatment, according to research by Bull et al. (2011), in the USA [38]. Surgical intervention may also be required for gastrointestinal issues, such as a tracheoesophageal fistula, duodenal blockage, Hirschsprung disease, and imperforate anus [39]. In an analysis of hospital admissions for patients aged 0–19 years in Australia, Dye et al. (2010) discovered that patients with genetic diseases, such as DS, had higher admissions and were in the hospital longer than patients admitted for every cause [40]. As patients with DS age, however, the relationship between age and costs alters, such that costs increase with older age. Thyroid problems, cervical spine disease, hearing impairment, obesity, sleep apnea, heart disease, and osteopenia–osteoporosis are all linked to aging in DS [3], which drives increases in costs as people with DS age.

4.4. Socioeconomic Characteristics

Socioeconomic variables reported by included studies to be associated with healthcare costs borne by individuals, families and society included socioeconomic status, urban vs. rural geographical location, and ethnicity. Families and individuals with DS who reside in urban areas incur greater cost than those in rural areas, which may reflect improved access to diagnosis, treatment, rehabilitation, and other health and welfare facilities in urban areas compared to rural areas. On the other hand, Deng et al. (2015) found that prenatal diagnosis were performed more frequently in urban areas than in rural areas and due to the higher social and economic status of urban women and their greater access to healthcare services, the total prevalence of Down syndrome in urban areas is higher than in rural areas [41]. It should be mentioned that adequate prenatal screening policies may minimize lifelong costs to people, families, and society [42, 43]. However, studies reveal that low socioeconomic status (SES) is associated with diminished DS screening uptake [44, 45].

Ethnic disparities also play a critical role in the economic burden of DS. In the United States, Hispanic and African American children with DS are more likely to rely on informal care, face higher hospitalization rates, and experience longer hospital stays compared to their white counterparts [46]. These disparities highlight the need for culturally sensitive healthcare policies and support systems that address the unique challenges faced by these populations.

Also, Racial or ethnic variations have been found to influence risk perception and attitudes toward prenatal testing strategies, which result in variation in prevalence of DS across different ethnic groups, and thus cost differences between ethnic groups [45]. Furthermore, race and ethnicity have been shown to have an impact on infant, child, and adult mortality trends and age at death, which has an impact on indirect costs such as productivity losses [37]. However, studies have yet to clearly identify those ethnic groups that incur greater costs or to disentangle the impact of health status, socio‐economic status, and cultural beliefs on cost differences, and further research in this area is needed.

Low socioeconomic status was a further factor reported by included studies to contribute to the higher cost of DS. According to Khan et al. (2006), parents of children with DS who work in the informal sector are more likely to have low socioeconomic status than those who do not [47]. Similarly, Ruger et al. (2001), in the US, suggest that DS imposes a financial strain on people with DS and their families, which has a knock‐on impact on society more broadly. Because of the burden of disease of DS, individuals with DS and their families are likely to invest less in the accumulation of human capital, which may have a negative effect on family income [48], and additionally bear significant financial burden related to care needs [17, 36].

In addition to the cost of healthcare, families incur additional socioeconomic burdens as a result of caring for a family member with DS. Included studies reveled that there is a linear association between age and the hours invested in the care of children with DS, with care needs increasing with ageing. Parents were the primary caregivers in 73% of DS patients, as reported by de Asua et al. (2015) [49], and health, independence, and physical ability of children with DS influence families as a main caregivers in different ways [50]. This implies that family members of people with DS are likely to have less time to devote to productive employment, which will have a negative impact on family income [51].

DS also impacts on the education received. Whilst mainstream schools are appropriate for some children with DS, those with more severe functional disabilities and comorbidities may require more specialized schools. Lack of access to such schools can have a deleterious impact on the children, who may not receive an appropriate education, but also on family members who may have to sacrifice employment to care for a child at home. Many countries offer governmental infrastructure and social services to enable children with DS to attend school to promote self‐care among children, and minimize families' indirect costs [46].

As Grosse (2010) notes in his study, non‐economic aspects such as emotional considerations, values, time constraints, or other social circumstances are not investigated in studies due to a lack of data and the intricacy of the considerations and computations. However, parents frequently regard these elements as critical difficulties, affecting the indirect cost [52].

Cross‐country differences in reported healthcare costs should be interpreted in the context of underlying healthcare financing systems. Studies from the United States consistently reported higher absolute costs, particularly for inpatient and hospital‐based services, which likely reflect higher unit prices, private insurance reimbursement mechanisms, and greater cost‐sharing compared with tax‐funded or single‐payer systems. In contrast, studies from countries with national health insurance or publicly funded healthcare systems, such as Canada, Australia, and Taiwan, reported lower direct healthcare costs, potentially due to regulated provider fees, stronger primary care gatekeeping, and broader coverage of essential services. These structural differences in health system financing and service delivery are likely to be key drivers of the observed international variation in cost estimates.

Although this review focused specifically on DS, comparison with the broader literature on intellectual and developmental disabilities provides important context for interpreting the observed cost patterns. Studies of conditions such as autism spectrum disorder, cerebral palsy, and non‐specific intellectual disability consistently report substantially higher healthcare and societal costs than those of the general population, with indirect costs—particularly productivity losses and caregiver time—accounting for a large proportion of the total economic burden [53, 54]. Similar to DS, families of individuals with other IDDs experience long‐term financial strain due to ongoing care needs, reduced labor force participation, and reliance on informal caregiving [55]. These shared cost drivers suggest that DS fits within a broader pattern of elevated economic burden observed across IDDs, particularly with respect to indirect and family‐borne costs.

However, the structure and timing of costs in DS appear to be distinctive. DS is characterized by a pronounced early‐life peak in direct medical costs, largely driven by congenital anomalies—especially congenital heart defects and gastrointestinal malformations—that frequently require surgical intervention and prolonged hospitalization during infancy [56, 57]. In contrast, healthcare costs for many other IDDs, such as autism spectrum disorder, tend to accumulate more gradually over childhood and are more strongly driven by outpatient services, behavioral therapies, and educational supports rather than acute inpatient care [53, 54]. In later life, individuals with DS often experience a second increase in healthcare expenditures due to accelerated aging and a higher prevalence of age‐related comorbidities, including Alzheimer‐type dementia and multimorbidity, a pattern less pronounced in many other IDDs [58]. Together, these findings indicate that while DS shares common economic challenges with other IDDs, it follows a distinct life‐course cost trajectory, underscoring the need for condition‐specific long‐term health and social care planning.

Overall, healthcare providers can leverage the findings of this systematic review to improve care coordination and reduce unnecessary costs, especially in high‐cost areas like inpatient services, by implementing integrated care models that bring together multidisciplinary teams, developing personalized care plans using electronic health records, and utilizing telemedicine for routine follow‐ups and remote monitoring. Emphasizing preventive care and early intervention, expanding access to outpatient and community‐based services, and establishing protocols for efficient use of inpatient services can prevent complications and reduce hospital admissions.

Additionally, data‐driven decision making and patient and family engagement are crucial for identifying high‐cost areas, targeting effective interventions, and ensuring smooth transitions from hospital to home or community care, ultimately enhancing patient outcomes and quality of life while optimizing resource utilization.

4.5. Policy Implications

Based on the findings of the study on the economic burden of Down syndrome (DS), some detailed policy implications have provided to improve access to healthcare among people with DS.

Given that inpatient services constituted the largest share of direct costs in 58% of studies, governments and healthcare systems should develop comprehensive, long‐term policies that address both direct and indirect costs, including integrating medical, social, and educational support services to provide holistic care for individuals with DS and their families.

Recognizing that productivity losses drive 25% of indirect costs, policymakers should focus on targeted interventions such as enhancing outpatient care and community‐based services to reduce reliance on inpatient services, thereby lowering healthcare costs.

Support schemes for families: The economic burden on families of individuals with DS is substantial. Policy measures should include financial support schemes such as subsidies, tax breaks, or direct financial assistance to alleviate the financial strain on families. Additionally, providing access to affordable childcare and respite care services can help families balance their caregiving responsibilities and work.

Enhanced early intervention programs: Investing in early intervention programs can help mitigate long‐term costs by addressing developmental delays and health issues early in life. Policies should support the expansion and accessibility of early intervention services, ensuring that all children with DS receive timely and appropriate care.

Insurance coverage and healthcare financing: Policies should ensure comprehensive insurance coverage for individuals with DS, covering a wide range of medical, therapeutic, and support services. This can help reduce out‐of‐pocket expenses for families and ensure consistent access to necessary care.

Investment in research and data collection: There is a need for ongoing research and data collection to better understand the long‐term economic impact of DS and the effectiveness of various interventions. Policymakers should invest in research initiatives and establish databases to track healthcare costs, outcomes, and quality of life for individuals with DS.

Public awareness and education campaigns: Increasing public awareness about DS and the associated economic challenges can help garner support for relevant policies and programs. Educational campaigns can also reduce stigma and promote inclusion, improving the overall quality of life for individuals with DS.

5. Limitations

This research has certain limitations. To begin, we could not compare overall healthcare expenditures and out‐of‐pocket expenses across included research because each study included a distinct set of cost components and reported results from different years in different currencies. Because healthcare delivery and finance systems in the included research varied, it was impossible to meaningfully compare healthcare costs across nations.

Second, we excluded gray literature and papers written in languages other than English, which may have led to publication bias, under‐representation of evidence from low‐ and middle‐income countries (e.g., non‐English reports from Latin America or Asia), and omission of potentially relevant cost data from theses, reports, or policy documents.

6. Conclusion

This systematic review reveals that indirect costs, alongside direct healthcare expenses, constitute a significant portion of the overall financial burden faced by individuals with Down syndrome (DS) and their families. Key determinants of these costs include age, associated morbidities, functional impairments, and socioeconomic status. Our findings underscore the need for comprehensive strategies to reduce both direct and indirect costs for these families. Long‐term plans should be developed that integrate medical and social welfare programs specifically tailored for individuals with DS. These plans should encompass healthcare and insurance improvements to ensure better access to necessary services and robust community support to alleviate the pressure on family members, allowing them to better manage the demands of caring for individuals with DS.

Additionally, targeted management of co‐morbid conditions is essential to mitigate both direct and indirect costs. Preventive measures, such as prenatal screening programs and informational campaigns for women of reproductive age, are also crucial in reducing the incidence of DS, thereby lessening the financial burden on families and the healthcare system. By adopting these comprehensive and proactive measures, governments can significantly reduce the economic impact of DS on families and society, enhancing the quality of life for individuals with DS.

Author Contributions

Shiva Tolouei Rakhshan: conceptualization, methodology, validation, investigation, formal analysis, writing – original draft, writing – review and editing, visualization. Sarah Byford: methodology, validation, investigation, writing – review and editing, writing – original draft, supervision. Mahya Razimoghadam: data curation, validation, investigation, writing – review and editing, writing – original draft. Fardin Moradi: data curation, formal analysis, writing – review and editing, writing – original draft, methodology, software. Shahin Soltani: conceptualization, methodology, supervision, formal analysis, project administration, writing – original draft, writing – review and editing, validation.

Ethics Statement

This study was approved by the ethics committee of Kermanshah University of Medical Sciences (IR.KUMS.REC.1398.491).

Consent

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Transparency Statement

The lead author Shahin Soltani affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.