Medication dispensing among Māori and non-Māori screened for preschool ADHD
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Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition characterised by symptoms of hyperactivity, inattention and impulsivity, with an estimated worldwide prevalence of 3.4%.[[1]] It is usually diagnosed in early childhood, is more common in boys than girls and has both environmental and genetic influences.[[2,3]] In Aotearoa New Zealand, behavioural parent training is the first-line treatment recommended for childhood ADHD.[[4]] For school-age children with moderate or severe symptoms medication can also be prescribed.[[4]]
Children with a diagnosis of ADHD are significantly more likely to experience adverse outcomes, including anti-social behaviour and drug use, criminal convictions, mental health difficulties, poorer physical health and negative academic and occupational outcomes.[[5,6]] It is important to identify children with symptoms indicative of ADHD to facilitate early identification and treatment and to mitigate the risk of poorer long-term outcomes.[[6]] In the New Zealand context, the Before School Check (B4SC)—a nationwide pre-school health screening check offered to all New Zealand children at 4 years of age—is one way to identify children with social, emotional and behavioural challenges (including ADHD symptoms) earlier in development. The B4SC is reported to have screened 92% of all eligible 4-year-olds in New Zealand.[[7]]
The B4SC asks caregivers and early childhood teachers to complete the Strengths and Difficulties Questionnaire (SDQ), a brief 25-item questionnaire designed to screen for possible emotional and behavioural difficulties in children aged 4–17-years of age.[[8]] The hyperactivity-inattention subscale of the SDQ can be used to indicate the severity of ADHD-like behaviours. A range of behavioural information from the B4SC, including SDQ scores, are used to determine whether children should be referred on for specialist follow-up for formal diagnosis and treatment by a paediatrician, clinical psychologist or psychiatrist.[[9]]
Given the long-term effects of untreated ADHD,[[6]] it is important to investigate whether early screening and intervention results in equitable outcomes for all New Zealanders. Previous research has indicated that Māori may not be receiving adequate healthcare, due to barriers in accessing care or negative healthcare experiences.[[10–14]] There is limited information on whether this is also the case for ADHD, with no specific research investigating equitable access to ADHD treatment for Māori. There are limited data available on ADHD treatments in Aotearoa New Zealand, though investigation into pharmacological treatment can be conducted using administrative data on pharmaceutical dispensings.[[15]] Using such data, the current study aimed to investigate whether tamariki Māori screened for ADHD concerns in the B4SC are as likely to receive medication relative to non-Māori children.
Methods
Study population
Data for this study were obtained from the Integrated Data Infrastructure (IDI), a large whole-population research database managed by Statistics New Zealand containing linked de-identified administrative data about people and households.[[16]] The study population consisted of all children aged 48–60 months who participated in the B4SC between 1 January 2011 to 31 December 2018. Children were excluded from our study if they had missing SDQ or referral information (n=4,350). As the current study aimed to investigate the treatment provided following screening in Māori and non-Māori children, children were also excluded if parents indicated that their child was under the care of a specialist for a behaviour-related condition (n=8,436) or if they had missing ethnicity information (n=120). The final sample consisted of 414,171 children.
Measures
ADHD concerns
In the B4SC, the SDQ[[8]] was completed by parents and, where possible, teachers. As the B4SC behavioural referral is based on a variety of information, including SDQ scores, and does not indicate whether the child received a referral specifically for hyperactivity-inattention,[[9]] we used both the SDQ hyperactivity-inattention score (which ranges from 0 to 10) and referral information together to define the ADHD concerns category. Specifically, using either parent- or teacher-rated SDQ data, children were categorised as having ADHD concerns if they had a behavioural referral and a borderline or above hyperactivity score based on pre-determined cut-offs (i.e., a score of 6 or above).[[8]] All other children were categorised as not showing ADHD concerns.
ADHD medication dispensing
Dispensing for ADHD medication was drawn from the Ministry of Health community pharmaceutical dispensing collection. Children were classified as receiving ADHD medication if they had at least one ADHD medication dispensing after completion of their B4SC and before 31 December 2019 (the latest date for pharmaceutical data availability at the time of analysis). Medications of interest were atomoxetine, dexamphetamine sulphate, methylphenidate hydrochloride (immediate- and extended-release), modafinil, and clonidine. All medications except clonidine are public-funded stimulant/ADHD medications.[[17]] Clonidine was included in the current study as it is also prescribed (but not subsidised) to treat ADHD in Aotearoa New Zealand.[[18]]
Socio-demographic variables
Sex (male/female) and ethnicity (Māori/non-Māori) were sourced from the personal details table in the IDI. Socio-economic status was established using the 2013 New Zealand Deprivation Index (NZDep2013),[[19]] an area-level measure of deprivation. The NZDep2013 assigns to “meshblocks” (small areas containing 30–60 households) a deprivation decile value ranging from 1 (least deprived) to 10 (most deprived) based on socio-economic indicators from the 2013 New Zealand Census. Meshblocks were identified from residential information at the time of the B4SC, and sourced from the address notification table within the IDI. For the current study, deprivation scores were converted into quintiles. Address notifications were also used to determine the urban/rural profile for participants’ residences.[[20]] This was categorised into a 5-level variable, based on area population sizes: major urban areas (populations of 100,000 or more); large urban areas (30,000–99,999); medium urban areas (10,000–29,999); small urban areas (1,000–9,999) and rural areas (<1,000).
Data analysis
IDI data were extracted using SAS Enterprise Guide 7.1 and analysed using Stata MP version 16. As per the confidentiality requirements of Statistics New Zealand, all counts have been random rounded to base 3. Percentages given are calculated from random rounded counts.
To evaluate the predictive validity of ADHD concerns screened through the B4SC, a cox proportional hazards analysis was conducted by regressing ADHD medication dispensing on ADHD concerns, controlling for Māori ethnicity, sex, area-level deprivation, urban/rural profile and participants’ birth year.
To determine whether ADHD medication dispensing differed for Māori screened for ADHD concerns relative to non-Māori, a cox proportion hazards analysis was conducted among those in the ADHD concerns category, with Māori ethnicity included in the model as a predictor. The adjusted analysis controlled for sex, area-level deprivation, urban/rural profile and year of birth. The cox proportional hazards model was right-censored for death, international departure for over a year, or 31 December 2019 (the end of our study period) if no dispensing was received. Unadjusted hazard ratios (HRs) and adjusted hazard ratios (AHRs) with 95% confidence intervals (CIs) have been reported.
Results
Descriptive statistics
In our sample of 414,171 individuals, 27% identifed as Māori (n=111,288). The average follow-up time from date of B4SC until the end of the study period (31 December 2019) was 1,809 days (SD=823) or 5.00 years for Māori and 1,773 days (SD=825) or 4.86 years for non-Māori.
View Tables 1–3.
Descriptive statistics for the final sample (after exclusions) are presented in Table 1. These results show that the proportion of males and females were evenly distributed for both Māori and non-Māori. There was a greater proportion of tamariki Māori living in more deprived areas relative to non-Māori. The greatest proportion of children lived in major urban areas, though this percentage was larger for non-Māori. Tamariki Māori were more likely to live in large urban areas and also small urban areas.
Of those with SDQ data, 99.7% of Māori and non-Māori children had parent-rated scores. Non-Māori children were more likely than tamariki Māori to have teacher-rated SDQ data.
The percentage of Māori and non-Māori children meeting the criteria for ADHD concerns, defined as those who had a behavioural referral and a borderline or above hyperactivity score, are presented in Table 2 for the overall population and by socio-demographic characteristics. The results show that 2.8% of tamariki Māori and 1.6% of non-Māori children met the criteria for ADHD concerns. A greater proportion of tamariki Māori met the criteria for ADHD concerns relative to non-Māori children for all socio-demographic groups. Across both Māori and non-Māori children, males were more likely to meet the criteria for ADHD concerns, as were those in more deprived areas. There was no clear pattern by urban/rural profile or residence.
Table 2 also displays the proportion of Māori and non-Māori children with ADHD concerns who received a dispensing for ADHD medication following completion of the B4SC. Among Māori, 10.8% of those with ADHD concerns received medication. Among non-Māori, 14.9% received medication. Across Māori and non-Māori children, males were more likely to have received medication than females, though a lower medication rate was also observed in Māori when stratifying by sex. However, the pattern of less medication in Māori is not uniformly observed across all socio-demographic characteristics. When examining medication rates by area-level deprivation in those with ADHD concerns, this pattern of difference between Māori and non-Māori is only apparent in the most deprived quintile, with marginal differences observed in other quintiles. Further, this quintile had the lowest medication rate for tamariki Māori but the greatest medication rate among non-Māori children. With medication rates by urban/rural profile or residence, a similar proportion of Māori and non-Māori living in major urban areas were dispensed medication. In other urban/rural locations, fewer Māori were dispensed medication relative to non-Māori. The lowest medication rate was observed in major urban areas for non-Māori, but in small urban areas for Māori.
Cox proportional hazard analyses
Having ADHD concerns was strongly predictive of ADHD medication dispensing in the unadjusted cox proportions hazards model (HR=10.13 [95% CI: 9.48–10.82]). This effect was attenuated but still strong in the adjusted model (AHR=7.93 [95% CI: 7.41-8.49]).
As shown in Table 3, the unadjusted analysis in children identified as having ADHD concerns indicated that Māori had a lower likelihood of being dispensed an ADHD medication relative to non-Māori, as evidenced by a hazard ratio significantly less than 1 (HR=0.67 [0.59–0.76]). This effect remained unchanged following adjustment of socio-demographic characteristics (AHR=0.67 [0.58–0.77]).
As we observed different patterns in the medication rate for Māori and non-Māori by deprivation quintile and urban/rural profile, we explored whether these socio-demographic factors had a moderating effect on the association between Māori ethnicity and ADHD medication dispensing. Unadjusted and adjusted hazard ratios for Māori ethnicity, stratified by area-level deprivation and urban/rural profile, are also presented in Table 3. Results indicated no significant difference in ADHD medication dispensing between Māori and non-Māori with ADHD concerns living in quintiles 1–4, but showed a lower likelihood of receiving medication for Māori living in the most deprived quintile (HR=0.47 [0.38, 0.58], AHR=0.45 [0.36, 0.56]). Unadjusted and adjusted analyses by urban/rural profile showed no significant difference in ADHD medication dispensing between Māori and non-Māori living in major urban areas, but a lower likelihood of medication dispensing for Māori living in all other areas (HR=0.56 [0.48, 0.66], AHR=0.60 [0.51, 0.71]).
Discussion
The current study investigated whether tamariki Māori with ADHD concerns were as likely to receive medication treatment as non-Māori. In our national cohort of 414,171 children who participated in the B4SC over a 7-year period (2011–2018), 2.8% of Māori and 1.6% of non-Māori were identified as exhibiting ADHD concerns. However, fewer Māori with ADHD concerns received medication (10.8%) compared to non-Māori (14.9%). Cox proportional hazard analyses also revealed that, among those with ADHD concerns, Māori had a significantly lower likelihood of ADHD medication dispensing when compared to non-Māori. Further investigation indicated that this difference was only significant among those living in the most deprived quintile of area-level deprivation and outside of major urban areas.
There are several potential factors contributing to the gap in medication use between Māori and non-Māori. Firstly, the ongoing impact of colonisation and institutionalised racism may be contributing to a lack of trust in the healthcare system. Treatment for children screened for ADHD is dependent on the parents, who may have had previous negative experiences with healthcare and are therefore hesitant to include children in the system. There is evidence to suggest that Indigenous peoples have negative experiences when accessing healthcare, which can influence their decision to access services in future.[[10,14]] A lack of representation in the health workforce can further negatively impact on Māori engagement with health services, as compliance is reduced when the healthcare professional and client are from different cultural backgrounds.[[21]]
Secondly, we used the SDQ as a screening tool for probable ADHD. However, there have been cultural concerns raised about the SDQ.[[22–24]] These concerns focus on three areas: the manner in which the SDQ is conducted, including whether informants understand the questions;[[22]] the scoring thresholds;[[23,24]] and concerns that it does not accurately consider behaviours from children in the context of their culture.[[25]] As such, it is plausible that there may be tamariki Māori who scored highly on the hyperactivity-inattention subscale who do not have ADHD (and vice versa), due to the SDQ not being a culturally appropriate measure. Children misclassified as having ADHD concerns may then get correctly classified during the referral, resulting in no further treatment.
Thirdly, this reduced treatment amongst Māori may also be due to pharmacological treatment reflecting a more Western, biologically based model of health. Māori parents have reported concern about the use of Western medicines for tamariki, including conflicting cultural wellbeing models, price, a mistrust of Western services and a desire to have Indigenous-by and for-Māori approaches.[[26–28]] In a small, but comprehensive qualitative study of older Māori, Nikora and colleagues found that medication use was determined by a series of processes associated with culture, and the cost, time commitment and perceived necessity of medical consultations.[[29]] Therefore, it is plausible that Māori may choose to seek alternative, non-pharmacological treatment options instead of medication. However, given that we only observed a lower likelihood of ADHD medication dispensing for Māori living in the most deprived regions or outside of major urban areas, our results suggest that challenges with accessing treatment may be a key factor in driving the observed differences.
Addressing the inequity in timely access to ADHD treatment for Māori, particularly those living in more deprived and non-urban areas, is vital as delays in treatment may have a flow-on effect once tamariki start school. Research has shown that ADHD treatment, whether pharmacological, non-pharmacological or multimodal, improves academic productivity;[[6]] therefore, the absence of or delayed treatment may impact children’s educational outcomes, further exacerbating existing socio-economic inequities. As highlighted above, this differential access may be impacted by financial barriers, inadequate screening, culturally inappropriate treatment options or a lack of trust in the healthcare system. Key strategies to improve access can include a reduction in costs associated with assessments and prescription fills for ADHD, the incorporation of Māori models of health in treatment strategies, greater workforce development in culturally safe care and representation of Māori among mental health specialists.
There are limitations with the current study that need to be considered. We did not have access to clinical diagnoses of ADHD to evaluate the accuracy of the screening method used here; however, we can have some confidence in our method given that a classification of ADHD concerns was strongly predictive of a medication dispensing. The IDI only contains reliable information on pharmacological treatment accessed for ADHD, so we were unable to evaluate the use of other treatment options for ADHD, such as behavioural intervention and primary care. As stated previously, this may be a preferred option to pharmacological treatment for Māori families. However, there is also evidence of inequity in access to other forms of healthcare, such as primary care, for Māori.[[11,12]] It is imperitive to not only investigate whether similar disparities exist for other treatment options for ADHD in future research, but also ensure that Māori families are aware of and have access to all treatment options for ADHD and that these options are culturally safe.
There is also evidence of disparities in B4SC participation, with tamariki Māori and their whānau who may have difficulty accessing healthcare (e.g., due to living in socio-economically deprived areas or experiencing higher residential mobility) having lower participation rates.[[30]] Thus, while there has been generally high participation in the B4SC—92% of all children enrolled at a primary health organisation (PHO) participated in 2015/2016[[7]]—it may be that the tamariki most at risk are those who do not receive the B4SC screen.
The longitudinal nature of the IDI and ability to link individual records, such as the B4SC to pharmaceutical dispensings, was an advantage. This allowed us to determine whether the B4SC screening process is leading to similar follow up treatment outcomes across Māori and non-Māori.
The current study demonstrated that tamariki Māori identified as showing ADHD concerns had a lower likelihood of ADHD medication dispensing than non-Māori if they lived in highly deprived neighbourhoods or outside of major urban areas. It is imperative to reduce barriers in accessing healthcare to effectively reduce inequities in treatment for ADHD between Māori and non-Māori. Further research is needed to understand whether difference in treatment for ADHD extends to non-pharmacological treatment and what the specific barriers may be to accessing treatment for Māori.
Summary
Abstract
Aim
To investigate whether tamariki Māori screened for attention-deficit/hyperactivity disorder (ADHD) concerns in the B4 School Check (B4SC) between 2011 to 2018 are as likely to receive ADHD medication as non-Māori children.
Method
Using population-level data from the Integrated Data Infrastructure, we investigated whether ADHD medication dispensing differed for tamariki Māori screened for ADHD concerns relative to non-Māori children. Analyses were also stratified by area-level deprivation and urban/rural profile of residence.
Results
In our cohort of 414,171 children, 2.8% of Māori and 1.6% of non-Māori were screened as showing ADHD concerns. Among those with ADHD concerns, tamariki Māori had a lower likelihood of ADHD medication dispensing following the B4SC (10.8%) relative to non-Māori children (14.9%), but this effect was only significant among those living in the most deprived quintile and outside of major urban areas.
Conclusion
Our study indicates that inequities to accessing ADHD treatment may exist for tamariki Māori living in highly deprived neighbourhoods or outside of major urban areas. Further research is needed to understand what the specific barriers may be to accessing ADHD medication treatment for Māori in these areas.
Author Information
Acknowledgements
Correspondence
Correspondence Email
Competing Interests
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5) Thapar A, Cooper M. Attention deficit hyperactivity disorder. Lancet. 2016 Mar 19;387(10024):1240-50.
6) Shaw M, Hodgkins P, Caci H, et al. A systematic review and analysis of long-term outcomes in attention deficit hyperactivity disorder: effects of treatment and non-treatment. BMC Med. 2012 Sep 4;10(1):99.
7) Ministry of Health. B4 School Check information for the health sector [Internet]. Ministry of Health NZ. 2016 [cited 2018 Jan 18]. Available from: https://www.health.govt.nz/our-work/life-stages/child-health/b4-school-check/b4-school-check-information-health-sector.
8) Goodman R. The Strengths and Difficulties Questionnaire: a research note. J Child Psychol Psychiatry. 1997;38(5):581-6.
9) Ministry of Health. The B4 School Check: A handbook for practitioners. Wellington, New Zealand: Ministry of Health; 2008.
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Medication dispensing among Māori and non-Māori screened for preschool ADHD
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Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition characterised by symptoms of hyperactivity, inattention and impulsivity, with an estimated worldwide prevalence of 3.4%.[[1]] It is usually diagnosed in early childhood, is more common in boys than girls and has both environmental and genetic influences.[[2,3]] In Aotearoa New Zealand, behavioural parent training is the first-line treatment recommended for childhood ADHD.[[4]] For school-age children with moderate or severe symptoms medication can also be prescribed.[[4]]
Children with a diagnosis of ADHD are significantly more likely to experience adverse outcomes, including anti-social behaviour and drug use, criminal convictions, mental health difficulties, poorer physical health and negative academic and occupational outcomes.[[5,6]] It is important to identify children with symptoms indicative of ADHD to facilitate early identification and treatment and to mitigate the risk of poorer long-term outcomes.[[6]] In the New Zealand context, the Before School Check (B4SC)—a nationwide pre-school health screening check offered to all New Zealand children at 4 years of age—is one way to identify children with social, emotional and behavioural challenges (including ADHD symptoms) earlier in development. The B4SC is reported to have screened 92% of all eligible 4-year-olds in New Zealand.[[7]]
The B4SC asks caregivers and early childhood teachers to complete the Strengths and Difficulties Questionnaire (SDQ), a brief 25-item questionnaire designed to screen for possible emotional and behavioural difficulties in children aged 4–17-years of age.[[8]] The hyperactivity-inattention subscale of the SDQ can be used to indicate the severity of ADHD-like behaviours. A range of behavioural information from the B4SC, including SDQ scores, are used to determine whether children should be referred on for specialist follow-up for formal diagnosis and treatment by a paediatrician, clinical psychologist or psychiatrist.[[9]]
Given the long-term effects of untreated ADHD,[[6]] it is important to investigate whether early screening and intervention results in equitable outcomes for all New Zealanders. Previous research has indicated that Māori may not be receiving adequate healthcare, due to barriers in accessing care or negative healthcare experiences.[[10–14]] There is limited information on whether this is also the case for ADHD, with no specific research investigating equitable access to ADHD treatment for Māori. There are limited data available on ADHD treatments in Aotearoa New Zealand, though investigation into pharmacological treatment can be conducted using administrative data on pharmaceutical dispensings.[[15]] Using such data, the current study aimed to investigate whether tamariki Māori screened for ADHD concerns in the B4SC are as likely to receive medication relative to non-Māori children.
Methods
Study population
Data for this study were obtained from the Integrated Data Infrastructure (IDI), a large whole-population research database managed by Statistics New Zealand containing linked de-identified administrative data about people and households.[[16]] The study population consisted of all children aged 48–60 months who participated in the B4SC between 1 January 2011 to 31 December 2018. Children were excluded from our study if they had missing SDQ or referral information (n=4,350). As the current study aimed to investigate the treatment provided following screening in Māori and non-Māori children, children were also excluded if parents indicated that their child was under the care of a specialist for a behaviour-related condition (n=8,436) or if they had missing ethnicity information (n=120). The final sample consisted of 414,171 children.
Measures
ADHD concerns
In the B4SC, the SDQ[[8]] was completed by parents and, where possible, teachers. As the B4SC behavioural referral is based on a variety of information, including SDQ scores, and does not indicate whether the child received a referral specifically for hyperactivity-inattention,[[9]] we used both the SDQ hyperactivity-inattention score (which ranges from 0 to 10) and referral information together to define the ADHD concerns category. Specifically, using either parent- or teacher-rated SDQ data, children were categorised as having ADHD concerns if they had a behavioural referral and a borderline or above hyperactivity score based on pre-determined cut-offs (i.e., a score of 6 or above).[[8]] All other children were categorised as not showing ADHD concerns.
ADHD medication dispensing
Dispensing for ADHD medication was drawn from the Ministry of Health community pharmaceutical dispensing collection. Children were classified as receiving ADHD medication if they had at least one ADHD medication dispensing after completion of their B4SC and before 31 December 2019 (the latest date for pharmaceutical data availability at the time of analysis). Medications of interest were atomoxetine, dexamphetamine sulphate, methylphenidate hydrochloride (immediate- and extended-release), modafinil, and clonidine. All medications except clonidine are public-funded stimulant/ADHD medications.[[17]] Clonidine was included in the current study as it is also prescribed (but not subsidised) to treat ADHD in Aotearoa New Zealand.[[18]]
Socio-demographic variables
Sex (male/female) and ethnicity (Māori/non-Māori) were sourced from the personal details table in the IDI. Socio-economic status was established using the 2013 New Zealand Deprivation Index (NZDep2013),[[19]] an area-level measure of deprivation. The NZDep2013 assigns to “meshblocks” (small areas containing 30–60 households) a deprivation decile value ranging from 1 (least deprived) to 10 (most deprived) based on socio-economic indicators from the 2013 New Zealand Census. Meshblocks were identified from residential information at the time of the B4SC, and sourced from the address notification table within the IDI. For the current study, deprivation scores were converted into quintiles. Address notifications were also used to determine the urban/rural profile for participants’ residences.[[20]] This was categorised into a 5-level variable, based on area population sizes: major urban areas (populations of 100,000 or more); large urban areas (30,000–99,999); medium urban areas (10,000–29,999); small urban areas (1,000–9,999) and rural areas (<1,000).
Data analysis
IDI data were extracted using SAS Enterprise Guide 7.1 and analysed using Stata MP version 16. As per the confidentiality requirements of Statistics New Zealand, all counts have been random rounded to base 3. Percentages given are calculated from random rounded counts.
To evaluate the predictive validity of ADHD concerns screened through the B4SC, a cox proportional hazards analysis was conducted by regressing ADHD medication dispensing on ADHD concerns, controlling for Māori ethnicity, sex, area-level deprivation, urban/rural profile and participants’ birth year.
To determine whether ADHD medication dispensing differed for Māori screened for ADHD concerns relative to non-Māori, a cox proportion hazards analysis was conducted among those in the ADHD concerns category, with Māori ethnicity included in the model as a predictor. The adjusted analysis controlled for sex, area-level deprivation, urban/rural profile and year of birth. The cox proportional hazards model was right-censored for death, international departure for over a year, or 31 December 2019 (the end of our study period) if no dispensing was received. Unadjusted hazard ratios (HRs) and adjusted hazard ratios (AHRs) with 95% confidence intervals (CIs) have been reported.
Results
Descriptive statistics
In our sample of 414,171 individuals, 27% identifed as Māori (n=111,288). The average follow-up time from date of B4SC until the end of the study period (31 December 2019) was 1,809 days (SD=823) or 5.00 years for Māori and 1,773 days (SD=825) or 4.86 years for non-Māori.
View Tables 1–3.
Descriptive statistics for the final sample (after exclusions) are presented in Table 1. These results show that the proportion of males and females were evenly distributed for both Māori and non-Māori. There was a greater proportion of tamariki Māori living in more deprived areas relative to non-Māori. The greatest proportion of children lived in major urban areas, though this percentage was larger for non-Māori. Tamariki Māori were more likely to live in large urban areas and also small urban areas.
Of those with SDQ data, 99.7% of Māori and non-Māori children had parent-rated scores. Non-Māori children were more likely than tamariki Māori to have teacher-rated SDQ data.
The percentage of Māori and non-Māori children meeting the criteria for ADHD concerns, defined as those who had a behavioural referral and a borderline or above hyperactivity score, are presented in Table 2 for the overall population and by socio-demographic characteristics. The results show that 2.8% of tamariki Māori and 1.6% of non-Māori children met the criteria for ADHD concerns. A greater proportion of tamariki Māori met the criteria for ADHD concerns relative to non-Māori children for all socio-demographic groups. Across both Māori and non-Māori children, males were more likely to meet the criteria for ADHD concerns, as were those in more deprived areas. There was no clear pattern by urban/rural profile or residence.
Table 2 also displays the proportion of Māori and non-Māori children with ADHD concerns who received a dispensing for ADHD medication following completion of the B4SC. Among Māori, 10.8% of those with ADHD concerns received medication. Among non-Māori, 14.9% received medication. Across Māori and non-Māori children, males were more likely to have received medication than females, though a lower medication rate was also observed in Māori when stratifying by sex. However, the pattern of less medication in Māori is not uniformly observed across all socio-demographic characteristics. When examining medication rates by area-level deprivation in those with ADHD concerns, this pattern of difference between Māori and non-Māori is only apparent in the most deprived quintile, with marginal differences observed in other quintiles. Further, this quintile had the lowest medication rate for tamariki Māori but the greatest medication rate among non-Māori children. With medication rates by urban/rural profile or residence, a similar proportion of Māori and non-Māori living in major urban areas were dispensed medication. In other urban/rural locations, fewer Māori were dispensed medication relative to non-Māori. The lowest medication rate was observed in major urban areas for non-Māori, but in small urban areas for Māori.
Cox proportional hazard analyses
Having ADHD concerns was strongly predictive of ADHD medication dispensing in the unadjusted cox proportions hazards model (HR=10.13 [95% CI: 9.48–10.82]). This effect was attenuated but still strong in the adjusted model (AHR=7.93 [95% CI: 7.41-8.49]).
As shown in Table 3, the unadjusted analysis in children identified as having ADHD concerns indicated that Māori had a lower likelihood of being dispensed an ADHD medication relative to non-Māori, as evidenced by a hazard ratio significantly less than 1 (HR=0.67 [0.59–0.76]). This effect remained unchanged following adjustment of socio-demographic characteristics (AHR=0.67 [0.58–0.77]).
As we observed different patterns in the medication rate for Māori and non-Māori by deprivation quintile and urban/rural profile, we explored whether these socio-demographic factors had a moderating effect on the association between Māori ethnicity and ADHD medication dispensing. Unadjusted and adjusted hazard ratios for Māori ethnicity, stratified by area-level deprivation and urban/rural profile, are also presented in Table 3. Results indicated no significant difference in ADHD medication dispensing between Māori and non-Māori with ADHD concerns living in quintiles 1–4, but showed a lower likelihood of receiving medication for Māori living in the most deprived quintile (HR=0.47 [0.38, 0.58], AHR=0.45 [0.36, 0.56]). Unadjusted and adjusted analyses by urban/rural profile showed no significant difference in ADHD medication dispensing between Māori and non-Māori living in major urban areas, but a lower likelihood of medication dispensing for Māori living in all other areas (HR=0.56 [0.48, 0.66], AHR=0.60 [0.51, 0.71]).
Discussion
The current study investigated whether tamariki Māori with ADHD concerns were as likely to receive medication treatment as non-Māori. In our national cohort of 414,171 children who participated in the B4SC over a 7-year period (2011–2018), 2.8% of Māori and 1.6% of non-Māori were identified as exhibiting ADHD concerns. However, fewer Māori with ADHD concerns received medication (10.8%) compared to non-Māori (14.9%). Cox proportional hazard analyses also revealed that, among those with ADHD concerns, Māori had a significantly lower likelihood of ADHD medication dispensing when compared to non-Māori. Further investigation indicated that this difference was only significant among those living in the most deprived quintile of area-level deprivation and outside of major urban areas.
There are several potential factors contributing to the gap in medication use between Māori and non-Māori. Firstly, the ongoing impact of colonisation and institutionalised racism may be contributing to a lack of trust in the healthcare system. Treatment for children screened for ADHD is dependent on the parents, who may have had previous negative experiences with healthcare and are therefore hesitant to include children in the system. There is evidence to suggest that Indigenous peoples have negative experiences when accessing healthcare, which can influence their decision to access services in future.[[10,14]] A lack of representation in the health workforce can further negatively impact on Māori engagement with health services, as compliance is reduced when the healthcare professional and client are from different cultural backgrounds.[[21]]
Secondly, we used the SDQ as a screening tool for probable ADHD. However, there have been cultural concerns raised about the SDQ.[[22–24]] These concerns focus on three areas: the manner in which the SDQ is conducted, including whether informants understand the questions;[[22]] the scoring thresholds;[[23,24]] and concerns that it does not accurately consider behaviours from children in the context of their culture.[[25]] As such, it is plausible that there may be tamariki Māori who scored highly on the hyperactivity-inattention subscale who do not have ADHD (and vice versa), due to the SDQ not being a culturally appropriate measure. Children misclassified as having ADHD concerns may then get correctly classified during the referral, resulting in no further treatment.
Thirdly, this reduced treatment amongst Māori may also be due to pharmacological treatment reflecting a more Western, biologically based model of health. Māori parents have reported concern about the use of Western medicines for tamariki, including conflicting cultural wellbeing models, price, a mistrust of Western services and a desire to have Indigenous-by and for-Māori approaches.[[26–28]] In a small, but comprehensive qualitative study of older Māori, Nikora and colleagues found that medication use was determined by a series of processes associated with culture, and the cost, time commitment and perceived necessity of medical consultations.[[29]] Therefore, it is plausible that Māori may choose to seek alternative, non-pharmacological treatment options instead of medication. However, given that we only observed a lower likelihood of ADHD medication dispensing for Māori living in the most deprived regions or outside of major urban areas, our results suggest that challenges with accessing treatment may be a key factor in driving the observed differences.
Addressing the inequity in timely access to ADHD treatment for Māori, particularly those living in more deprived and non-urban areas, is vital as delays in treatment may have a flow-on effect once tamariki start school. Research has shown that ADHD treatment, whether pharmacological, non-pharmacological or multimodal, improves academic productivity;[[6]] therefore, the absence of or delayed treatment may impact children’s educational outcomes, further exacerbating existing socio-economic inequities. As highlighted above, this differential access may be impacted by financial barriers, inadequate screening, culturally inappropriate treatment options or a lack of trust in the healthcare system. Key strategies to improve access can include a reduction in costs associated with assessments and prescription fills for ADHD, the incorporation of Māori models of health in treatment strategies, greater workforce development in culturally safe care and representation of Māori among mental health specialists.
There are limitations with the current study that need to be considered. We did not have access to clinical diagnoses of ADHD to evaluate the accuracy of the screening method used here; however, we can have some confidence in our method given that a classification of ADHD concerns was strongly predictive of a medication dispensing. The IDI only contains reliable information on pharmacological treatment accessed for ADHD, so we were unable to evaluate the use of other treatment options for ADHD, such as behavioural intervention and primary care. As stated previously, this may be a preferred option to pharmacological treatment for Māori families. However, there is also evidence of inequity in access to other forms of healthcare, such as primary care, for Māori.[[11,12]] It is imperitive to not only investigate whether similar disparities exist for other treatment options for ADHD in future research, but also ensure that Māori families are aware of and have access to all treatment options for ADHD and that these options are culturally safe.
There is also evidence of disparities in B4SC participation, with tamariki Māori and their whānau who may have difficulty accessing healthcare (e.g., due to living in socio-economically deprived areas or experiencing higher residential mobility) having lower participation rates.[[30]] Thus, while there has been generally high participation in the B4SC—92% of all children enrolled at a primary health organisation (PHO) participated in 2015/2016[[7]]—it may be that the tamariki most at risk are those who do not receive the B4SC screen.
The longitudinal nature of the IDI and ability to link individual records, such as the B4SC to pharmaceutical dispensings, was an advantage. This allowed us to determine whether the B4SC screening process is leading to similar follow up treatment outcomes across Māori and non-Māori.
The current study demonstrated that tamariki Māori identified as showing ADHD concerns had a lower likelihood of ADHD medication dispensing than non-Māori if they lived in highly deprived neighbourhoods or outside of major urban areas. It is imperative to reduce barriers in accessing healthcare to effectively reduce inequities in treatment for ADHD between Māori and non-Māori. Further research is needed to understand whether difference in treatment for ADHD extends to non-pharmacological treatment and what the specific barriers may be to accessing treatment for Māori.
Summary
Abstract
Aim
To investigate whether tamariki Māori screened for attention-deficit/hyperactivity disorder (ADHD) concerns in the B4 School Check (B4SC) between 2011 to 2018 are as likely to receive ADHD medication as non-Māori children.
Method
Using population-level data from the Integrated Data Infrastructure, we investigated whether ADHD medication dispensing differed for tamariki Māori screened for ADHD concerns relative to non-Māori children. Analyses were also stratified by area-level deprivation and urban/rural profile of residence.
Results
In our cohort of 414,171 children, 2.8% of Māori and 1.6% of non-Māori were screened as showing ADHD concerns. Among those with ADHD concerns, tamariki Māori had a lower likelihood of ADHD medication dispensing following the B4SC (10.8%) relative to non-Māori children (14.9%), but this effect was only significant among those living in the most deprived quintile and outside of major urban areas.
Conclusion
Our study indicates that inequities to accessing ADHD treatment may exist for tamariki Māori living in highly deprived neighbourhoods or outside of major urban areas. Further research is needed to understand what the specific barriers may be to accessing ADHD medication treatment for Māori in these areas.
Author Information
Acknowledgements
Correspondence
Correspondence Email
Competing Interests
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Medication dispensing among Māori and non-Māori screened for preschool ADHD
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Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition characterised by symptoms of hyperactivity, inattention and impulsivity, with an estimated worldwide prevalence of 3.4%.[[1]] It is usually diagnosed in early childhood, is more common in boys than girls and has both environmental and genetic influences.[[2,3]] In Aotearoa New Zealand, behavioural parent training is the first-line treatment recommended for childhood ADHD.[[4]] For school-age children with moderate or severe symptoms medication can also be prescribed.[[4]]
Children with a diagnosis of ADHD are significantly more likely to experience adverse outcomes, including anti-social behaviour and drug use, criminal convictions, mental health difficulties, poorer physical health and negative academic and occupational outcomes.[[5,6]] It is important to identify children with symptoms indicative of ADHD to facilitate early identification and treatment and to mitigate the risk of poorer long-term outcomes.[[6]] In the New Zealand context, the Before School Check (B4SC)—a nationwide pre-school health screening check offered to all New Zealand children at 4 years of age—is one way to identify children with social, emotional and behavioural challenges (including ADHD symptoms) earlier in development. The B4SC is reported to have screened 92% of all eligible 4-year-olds in New Zealand.[[7]]
The B4SC asks caregivers and early childhood teachers to complete the Strengths and Difficulties Questionnaire (SDQ), a brief 25-item questionnaire designed to screen for possible emotional and behavioural difficulties in children aged 4–17-years of age.[[8]] The hyperactivity-inattention subscale of the SDQ can be used to indicate the severity of ADHD-like behaviours. A range of behavioural information from the B4SC, including SDQ scores, are used to determine whether children should be referred on for specialist follow-up for formal diagnosis and treatment by a paediatrician, clinical psychologist or psychiatrist.[[9]]
Given the long-term effects of untreated ADHD,[[6]] it is important to investigate whether early screening and intervention results in equitable outcomes for all New Zealanders. Previous research has indicated that Māori may not be receiving adequate healthcare, due to barriers in accessing care or negative healthcare experiences.[[10–14]] There is limited information on whether this is also the case for ADHD, with no specific research investigating equitable access to ADHD treatment for Māori. There are limited data available on ADHD treatments in Aotearoa New Zealand, though investigation into pharmacological treatment can be conducted using administrative data on pharmaceutical dispensings.[[15]] Using such data, the current study aimed to investigate whether tamariki Māori screened for ADHD concerns in the B4SC are as likely to receive medication relative to non-Māori children.
Methods
Study population
Data for this study were obtained from the Integrated Data Infrastructure (IDI), a large whole-population research database managed by Statistics New Zealand containing linked de-identified administrative data about people and households.[[16]] The study population consisted of all children aged 48–60 months who participated in the B4SC between 1 January 2011 to 31 December 2018. Children were excluded from our study if they had missing SDQ or referral information (n=4,350). As the current study aimed to investigate the treatment provided following screening in Māori and non-Māori children, children were also excluded if parents indicated that their child was under the care of a specialist for a behaviour-related condition (n=8,436) or if they had missing ethnicity information (n=120). The final sample consisted of 414,171 children.
Measures
ADHD concerns
In the B4SC, the SDQ[[8]] was completed by parents and, where possible, teachers. As the B4SC behavioural referral is based on a variety of information, including SDQ scores, and does not indicate whether the child received a referral specifically for hyperactivity-inattention,[[9]] we used both the SDQ hyperactivity-inattention score (which ranges from 0 to 10) and referral information together to define the ADHD concerns category. Specifically, using either parent- or teacher-rated SDQ data, children were categorised as having ADHD concerns if they had a behavioural referral and a borderline or above hyperactivity score based on pre-determined cut-offs (i.e., a score of 6 or above).[[8]] All other children were categorised as not showing ADHD concerns.
ADHD medication dispensing
Dispensing for ADHD medication was drawn from the Ministry of Health community pharmaceutical dispensing collection. Children were classified as receiving ADHD medication if they had at least one ADHD medication dispensing after completion of their B4SC and before 31 December 2019 (the latest date for pharmaceutical data availability at the time of analysis). Medications of interest were atomoxetine, dexamphetamine sulphate, methylphenidate hydrochloride (immediate- and extended-release), modafinil, and clonidine. All medications except clonidine are public-funded stimulant/ADHD medications.[[17]] Clonidine was included in the current study as it is also prescribed (but not subsidised) to treat ADHD in Aotearoa New Zealand.[[18]]
Socio-demographic variables
Sex (male/female) and ethnicity (Māori/non-Māori) were sourced from the personal details table in the IDI. Socio-economic status was established using the 2013 New Zealand Deprivation Index (NZDep2013),[[19]] an area-level measure of deprivation. The NZDep2013 assigns to “meshblocks” (small areas containing 30–60 households) a deprivation decile value ranging from 1 (least deprived) to 10 (most deprived) based on socio-economic indicators from the 2013 New Zealand Census. Meshblocks were identified from residential information at the time of the B4SC, and sourced from the address notification table within the IDI. For the current study, deprivation scores were converted into quintiles. Address notifications were also used to determine the urban/rural profile for participants’ residences.[[20]] This was categorised into a 5-level variable, based on area population sizes: major urban areas (populations of 100,000 or more); large urban areas (30,000–99,999); medium urban areas (10,000–29,999); small urban areas (1,000–9,999) and rural areas (<1,000).
Data analysis
IDI data were extracted using SAS Enterprise Guide 7.1 and analysed using Stata MP version 16. As per the confidentiality requirements of Statistics New Zealand, all counts have been random rounded to base 3. Percentages given are calculated from random rounded counts.
To evaluate the predictive validity of ADHD concerns screened through the B4SC, a cox proportional hazards analysis was conducted by regressing ADHD medication dispensing on ADHD concerns, controlling for Māori ethnicity, sex, area-level deprivation, urban/rural profile and participants’ birth year.
To determine whether ADHD medication dispensing differed for Māori screened for ADHD concerns relative to non-Māori, a cox proportion hazards analysis was conducted among those in the ADHD concerns category, with Māori ethnicity included in the model as a predictor. The adjusted analysis controlled for sex, area-level deprivation, urban/rural profile and year of birth. The cox proportional hazards model was right-censored for death, international departure for over a year, or 31 December 2019 (the end of our study period) if no dispensing was received. Unadjusted hazard ratios (HRs) and adjusted hazard ratios (AHRs) with 95% confidence intervals (CIs) have been reported.
Results
Descriptive statistics
In our sample of 414,171 individuals, 27% identifed as Māori (n=111,288). The average follow-up time from date of B4SC until the end of the study period (31 December 2019) was 1,809 days (SD=823) or 5.00 years for Māori and 1,773 days (SD=825) or 4.86 years for non-Māori.
View Tables 1–3.
Descriptive statistics for the final sample (after exclusions) are presented in Table 1. These results show that the proportion of males and females were evenly distributed for both Māori and non-Māori. There was a greater proportion of tamariki Māori living in more deprived areas relative to non-Māori. The greatest proportion of children lived in major urban areas, though this percentage was larger for non-Māori. Tamariki Māori were more likely to live in large urban areas and also small urban areas.
Of those with SDQ data, 99.7% of Māori and non-Māori children had parent-rated scores. Non-Māori children were more likely than tamariki Māori to have teacher-rated SDQ data.
The percentage of Māori and non-Māori children meeting the criteria for ADHD concerns, defined as those who had a behavioural referral and a borderline or above hyperactivity score, are presented in Table 2 for the overall population and by socio-demographic characteristics. The results show that 2.8% of tamariki Māori and 1.6% of non-Māori children met the criteria for ADHD concerns. A greater proportion of tamariki Māori met the criteria for ADHD concerns relative to non-Māori children for all socio-demographic groups. Across both Māori and non-Māori children, males were more likely to meet the criteria for ADHD concerns, as were those in more deprived areas. There was no clear pattern by urban/rural profile or residence.
Table 2 also displays the proportion of Māori and non-Māori children with ADHD concerns who received a dispensing for ADHD medication following completion of the B4SC. Among Māori, 10.8% of those with ADHD concerns received medication. Among non-Māori, 14.9% received medication. Across Māori and non-Māori children, males were more likely to have received medication than females, though a lower medication rate was also observed in Māori when stratifying by sex. However, the pattern of less medication in Māori is not uniformly observed across all socio-demographic characteristics. When examining medication rates by area-level deprivation in those with ADHD concerns, this pattern of difference between Māori and non-Māori is only apparent in the most deprived quintile, with marginal differences observed in other quintiles. Further, this quintile had the lowest medication rate for tamariki Māori but the greatest medication rate among non-Māori children. With medication rates by urban/rural profile or residence, a similar proportion of Māori and non-Māori living in major urban areas were dispensed medication. In other urban/rural locations, fewer Māori were dispensed medication relative to non-Māori. The lowest medication rate was observed in major urban areas for non-Māori, but in small urban areas for Māori.
Cox proportional hazard analyses
Having ADHD concerns was strongly predictive of ADHD medication dispensing in the unadjusted cox proportions hazards model (HR=10.13 [95% CI: 9.48–10.82]). This effect was attenuated but still strong in the adjusted model (AHR=7.93 [95% CI: 7.41-8.49]).
As shown in Table 3, the unadjusted analysis in children identified as having ADHD concerns indicated that Māori had a lower likelihood of being dispensed an ADHD medication relative to non-Māori, as evidenced by a hazard ratio significantly less than 1 (HR=0.67 [0.59–0.76]). This effect remained unchanged following adjustment of socio-demographic characteristics (AHR=0.67 [0.58–0.77]).
As we observed different patterns in the medication rate for Māori and non-Māori by deprivation quintile and urban/rural profile, we explored whether these socio-demographic factors had a moderating effect on the association between Māori ethnicity and ADHD medication dispensing. Unadjusted and adjusted hazard ratios for Māori ethnicity, stratified by area-level deprivation and urban/rural profile, are also presented in Table 3. Results indicated no significant difference in ADHD medication dispensing between Māori and non-Māori with ADHD concerns living in quintiles 1–4, but showed a lower likelihood of receiving medication for Māori living in the most deprived quintile (HR=0.47 [0.38, 0.58], AHR=0.45 [0.36, 0.56]). Unadjusted and adjusted analyses by urban/rural profile showed no significant difference in ADHD medication dispensing between Māori and non-Māori living in major urban areas, but a lower likelihood of medication dispensing for Māori living in all other areas (HR=0.56 [0.48, 0.66], AHR=0.60 [0.51, 0.71]).
Discussion
The current study investigated whether tamariki Māori with ADHD concerns were as likely to receive medication treatment as non-Māori. In our national cohort of 414,171 children who participated in the B4SC over a 7-year period (2011–2018), 2.8% of Māori and 1.6% of non-Māori were identified as exhibiting ADHD concerns. However, fewer Māori with ADHD concerns received medication (10.8%) compared to non-Māori (14.9%). Cox proportional hazard analyses also revealed that, among those with ADHD concerns, Māori had a significantly lower likelihood of ADHD medication dispensing when compared to non-Māori. Further investigation indicated that this difference was only significant among those living in the most deprived quintile of area-level deprivation and outside of major urban areas.
There are several potential factors contributing to the gap in medication use between Māori and non-Māori. Firstly, the ongoing impact of colonisation and institutionalised racism may be contributing to a lack of trust in the healthcare system. Treatment for children screened for ADHD is dependent on the parents, who may have had previous negative experiences with healthcare and are therefore hesitant to include children in the system. There is evidence to suggest that Indigenous peoples have negative experiences when accessing healthcare, which can influence their decision to access services in future.[[10,14]] A lack of representation in the health workforce can further negatively impact on Māori engagement with health services, as compliance is reduced when the healthcare professional and client are from different cultural backgrounds.[[21]]
Secondly, we used the SDQ as a screening tool for probable ADHD. However, there have been cultural concerns raised about the SDQ.[[22–24]] These concerns focus on three areas: the manner in which the SDQ is conducted, including whether informants understand the questions;[[22]] the scoring thresholds;[[23,24]] and concerns that it does not accurately consider behaviours from children in the context of their culture.[[25]] As such, it is plausible that there may be tamariki Māori who scored highly on the hyperactivity-inattention subscale who do not have ADHD (and vice versa), due to the SDQ not being a culturally appropriate measure. Children misclassified as having ADHD concerns may then get correctly classified during the referral, resulting in no further treatment.
Thirdly, this reduced treatment amongst Māori may also be due to pharmacological treatment reflecting a more Western, biologically based model of health. Māori parents have reported concern about the use of Western medicines for tamariki, including conflicting cultural wellbeing models, price, a mistrust of Western services and a desire to have Indigenous-by and for-Māori approaches.[[26–28]] In a small, but comprehensive qualitative study of older Māori, Nikora and colleagues found that medication use was determined by a series of processes associated with culture, and the cost, time commitment and perceived necessity of medical consultations.[[29]] Therefore, it is plausible that Māori may choose to seek alternative, non-pharmacological treatment options instead of medication. However, given that we only observed a lower likelihood of ADHD medication dispensing for Māori living in the most deprived regions or outside of major urban areas, our results suggest that challenges with accessing treatment may be a key factor in driving the observed differences.
Addressing the inequity in timely access to ADHD treatment for Māori, particularly those living in more deprived and non-urban areas, is vital as delays in treatment may have a flow-on effect once tamariki start school. Research has shown that ADHD treatment, whether pharmacological, non-pharmacological or multimodal, improves academic productivity;[[6]] therefore, the absence of or delayed treatment may impact children’s educational outcomes, further exacerbating existing socio-economic inequities. As highlighted above, this differential access may be impacted by financial barriers, inadequate screening, culturally inappropriate treatment options or a lack of trust in the healthcare system. Key strategies to improve access can include a reduction in costs associated with assessments and prescription fills for ADHD, the incorporation of Māori models of health in treatment strategies, greater workforce development in culturally safe care and representation of Māori among mental health specialists.
There are limitations with the current study that need to be considered. We did not have access to clinical diagnoses of ADHD to evaluate the accuracy of the screening method used here; however, we can have some confidence in our method given that a classification of ADHD concerns was strongly predictive of a medication dispensing. The IDI only contains reliable information on pharmacological treatment accessed for ADHD, so we were unable to evaluate the use of other treatment options for ADHD, such as behavioural intervention and primary care. As stated previously, this may be a preferred option to pharmacological treatment for Māori families. However, there is also evidence of inequity in access to other forms of healthcare, such as primary care, for Māori.[[11,12]] It is imperitive to not only investigate whether similar disparities exist for other treatment options for ADHD in future research, but also ensure that Māori families are aware of and have access to all treatment options for ADHD and that these options are culturally safe.
There is also evidence of disparities in B4SC participation, with tamariki Māori and their whānau who may have difficulty accessing healthcare (e.g., due to living in socio-economically deprived areas or experiencing higher residential mobility) having lower participation rates.[[30]] Thus, while there has been generally high participation in the B4SC—92% of all children enrolled at a primary health organisation (PHO) participated in 2015/2016[[7]]—it may be that the tamariki most at risk are those who do not receive the B4SC screen.
The longitudinal nature of the IDI and ability to link individual records, such as the B4SC to pharmaceutical dispensings, was an advantage. This allowed us to determine whether the B4SC screening process is leading to similar follow up treatment outcomes across Māori and non-Māori.
The current study demonstrated that tamariki Māori identified as showing ADHD concerns had a lower likelihood of ADHD medication dispensing than non-Māori if they lived in highly deprived neighbourhoods or outside of major urban areas. It is imperative to reduce barriers in accessing healthcare to effectively reduce inequities in treatment for ADHD between Māori and non-Māori. Further research is needed to understand whether difference in treatment for ADHD extends to non-pharmacological treatment and what the specific barriers may be to accessing treatment for Māori.
Summary
Abstract
Aim
To investigate whether tamariki Māori screened for attention-deficit/hyperactivity disorder (ADHD) concerns in the B4 School Check (B4SC) between 2011 to 2018 are as likely to receive ADHD medication as non-Māori children.
Method
Using population-level data from the Integrated Data Infrastructure, we investigated whether ADHD medication dispensing differed for tamariki Māori screened for ADHD concerns relative to non-Māori children. Analyses were also stratified by area-level deprivation and urban/rural profile of residence.
Results
In our cohort of 414,171 children, 2.8% of Māori and 1.6% of non-Māori were screened as showing ADHD concerns. Among those with ADHD concerns, tamariki Māori had a lower likelihood of ADHD medication dispensing following the B4SC (10.8%) relative to non-Māori children (14.9%), but this effect was only significant among those living in the most deprived quintile and outside of major urban areas.
Conclusion
Our study indicates that inequities to accessing ADHD treatment may exist for tamariki Māori living in highly deprived neighbourhoods or outside of major urban areas. Further research is needed to understand what the specific barriers may be to accessing ADHD medication treatment for Māori in these areas.
Author Information
Acknowledgements
Correspondence
Correspondence Email
Competing Interests
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Medication dispensing among Māori and non-Māori screened for preschool ADHD
Children with a diagnosis of ADHD are significantly more likely to experience adverse outcomes, including anti-social behaviour and drug use, criminal convictions, mental health difficulties, poorer physical health and negative academic and occupational outcomes. It is important to identify children with symptoms indicative of ADHD to facilitate early identification and treatment and to mitigate the risk of poorer long-term outcomes.
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