Dataset Information

Health care for children with diabetes mellitus from low-income families in Ontario and California: a population-based cohort study.

ABSTRACT: Children with diabetes mellitus in low-income families have poor outcomes, but little is known as to how this relates to healthcare system structure. Our objective was to gain insight into how best to structure health systems to serve these children by describing their health care use in 2 health system models: a Canadian model, with an organized diabetes care network that includes generalists, and an American model, with targeted support services for children from low-income families.We performed a population-based retrospective cohort study involving children aged 1-17 years with type 1 diabetes mellitus. We used administrative data from between 2009 and 2012 from the California Children's Services program and Ontario. We used Ontario Drug Benefit Program enrolment to identify children from low-income families. Proportions of children receiving 2 or more routine diabetes visits per year were compared using ?2 tests, and diabetes-complication hospital admission rates were compared using direct standardization.More California children from low-income families (n = 4922) received routine care for diabetes from pediatric endocrinologists (63.9% v. 26.9%, p < 0.001) and used insulin pumps (22.8% v. 16.4%, p < 0.001) than Ontario children (n = 2050).California children from low-income families were less likely than Ontario children to receive 2 visits for routine diabetes care per year (64.7% v. 75.7%, p < 0.001), and had slightly higher per-patient year hospital admission rates for diabetes complications (absolute differences 0.02, 95% confidence interval [CI] 0.02-0.02, for boys; 0.03, 95% CI 0.03-0.03, for girls).Ontario children from low-income families received more routine diabetes care than did California children from low-income families. Both groups of children had clinically comparable rates of hospital admission for diabetes complications. Diabetes care networks that integrate generalists may play a role in improving access and outcomes for the growing population of children with diabetes.

SUBMITTER: Kaiser SV

PROVIDER: S-EPMC5173459 | biostudies-other | 2016 Oct-Dec

REPOSITORIES: biostudies-other

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Health care for children with diabetes mellitus from low-income families in Ontario and California: a population-based cohort study.

Kaiser Sunitha V SV Sundaram Vandana V Cohen Eyal E Shulman Rayzel R Guan Jun J Sanders Lee L Guttmann Astrid A

CMAJ open 20161001 4

<h4>Background</h4>Children with diabetes mellitus in low-income families have poor outcomes, but little is known as to how this relates to healthcare system structure. Our objective was to gain insight into how best to structure health systems to serve these children by describing their health care use in 2 health system models: a Canadian model, with an organized diabetes care network that includes generalists, and an American model, with targeted support services for children from low-income ...[more]

PMID: 28018888

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Project description:BackgroundIn Canada, more than 64 000 children are growing up with 1 or both parents in the military. We compared mental health service use by children and youth in military families versus the general population, to understand potential mental health service gaps.MethodsThis was a matched retrospective cohort study of children and youth (aged < 20 yr) of members of the Canadian Armed Forces posted to Ontario between Apr. 1, 2008, and Mar. 31, 2013, with follow-up to Mar. 31, 2017, using provincial administrative health data at ICES. We created a comparison group of children and youth in the general population, matched 4:1 by age, sex and geography. We compared the use and frequency of mental health-related physician visits, emergency department visits and hospital admissions, and the time to first service use, using regression models.ResultsThis study included 5478 children and youth in military families and a matched cohort of 21 912 children and youth in the general population. For visits and admissions for mental health reasons, children and youth in military families were more likely to see a family physician (adjusted relative risk [RR] 1.25, 95% confidence interval [CI] 1.17 to 1.34), less likely to see a pediatrician (adjusted RR 0.87, 95% CI 0.79 to 0.96), equally likely to see a psychiatrist, and as likely to visit an emergency department or be admitted to hospital as the matched cohort. Children and youth in military families had the same frequency of use of outpatient mental health services. The time to first visit for mental health reasons was shorter to see a family physician (adjusted days difference [DD] -57, 95% CI -80 to -33) and longer to see a psychiatrist (adjusted DD 103, 95% CI 43 to 163) for children and youth in military families.InterpretationChildren and youth in military families use mental health services differently from those in the general population. Provincial policies aimed at increasing access to mental health specialists for children and youth in military families, alongside targeted federal services and programming through military organizations, are needed.

Project description:ImportanceAn increasing diversity of children's health coverage options under the US Patient Protection and Affordable Care Act, together with uncertainty regarding reauthorization of the Children's Health Insurance Program (CHIP) beyond 2017, merits renewed attention on the quality of these options for children.ObjectiveTo compare health care access, quality, and cost outcomes by insurance type (Medicaid, CHIP, private, and uninsured) for children in households with low to moderate incomes.Design, setting, and participantsA repeated cross-sectional analysis was conducted using data from the 2003, 2007, and 2011-2012 US National Surveys of Children's Health, comprising 80,655 children 17 years or younger, weighted to 67 million children nationally, with household incomes between 100% and 300% of the federal poverty level. Multivariable logistic regression models compared caregiver-reported outcomes across insurance types. Analysis was conducted between July 14, 2014, and May 6, 2015.ExposuresInsurance type was ascertained using a caregiver-reported measure of insurance status and each household's poverty status (percentage of the federal poverty level).Main outcomes and measuresCaregiver-reported outcomes related to access to primary and specialty care, unmet needs, out-of-pocket costs, care coordination, and satisfaction with care.ResultsAmong the 80,655 children, 51,123 (57.3%) had private insurance, 11,853 (13.6%) had Medicaid, 9554 (18.4%) had CHIP, and 8125 (10.8%) were uninsured. In a multivariable logistic regression model (with results reported as adjusted probabilities [95% CIs]), children insured by Medicaid and CHIP were significantly more likely to receive a preventive medical (Medicaid, 88% [86%-89%]; P < .01; CHIP, 88% [87%-89%]; P < .01) and dental (Medicaid, 80% [78%-81%]; P < .01; CHIP, 77% [76%-79%]; P < .01) visits than were privately insured children (medical, 83% [82%-84%]; dental, 73% [72%-74%]). Children with all insurance types experienced challenges in access to specialty care, with caregivers of children insured by CHIP reporting the highest rates of difficulty accessing specialty care (28% [24%-32%]), problems obtaining a referral (23% [18%-29%]), and frustration obtaining health care services (26% [23%-28%]). These challenges were also magnified for privately insured children with special health care needs, whose caregivers reported significantly greater problems accessing specialty care (29% [26%-33%]) and frustration obtaining health care services (36% [32%-41%]) than did caregivers of children insured by Medicaid, and a lower likelihood of insurance always meeting the child's needs (63% [60%-67%]) than children insured by Medicaid or CHIP. Caregivers of privately insured children were also significantly more likely to experience out-of-pocket costs (77% [75%-78%]) than were caregivers of children insured by Medicaid (26% [23%-28%]; P < .01) or CHIP (38% [35%-40%]; P < .01).Conclusions and relevanceThis examination of caregiver experiences across insurance types revealed important differences that can help guide future policymaking regarding coverage for families with low to moderate incomes.

Project description:BackgroundStudies of effects of air pollution on gestational diabetes mellitus (GDM) have not been consistent, and there has been little investigation of effects of exposure preceding pregnancy. In previous studies, the temporal relationship between exposure and GDM onset has been difficult to establish.MethodsData were obtained for 239,574 pregnancies between 1999 and 2009 in a population-based health care system with comprehensive electronic medical records. Concentrations of ambient nitrogen dioxide (NO2), particulate matter (PM) ≤2.5 μm in aerodynamic diameter (PM2.5) and ≤10 μm (PM10), and ozone (O3) during preconception and the first trimester of pregnancy at the residential birth address were estimated from regulatory air monitoring stations. Odds ratios (ORs) of GDM diagnosed in the second and third trimesters in association with pollutant exposure were estimated using generalized estimating equation models adjusted for birth year, medical center service areas, maternal age, race/ethnicity, education, census-tract household income, and parity.ResultsIn single-pollutant models, preconception NO2 was associated with increased risk of GDM (OR = 1.10 per 10.4 ppb, 95% confidence interval [CI]: 1.07, 1.13). First trimester NO2 was weakly associated with GDM, and this was not statistically significant (OR = 1.02 per 10.4 ppb, 95% CI: 0.99, 1.05). Preconception NO2 associations were robust in multi-pollutant models adjusted for first trimester NO2 with another co-pollutant from both exposure windows. In single-pollutant models, preconception PM2.5 and PM10 associations were associated with increased risk of GDM (OR = 1.04 per 6.5 μg/m3, 95% CI: 1.01, 1.06; OR = 1.03 per 16.1 μg/m3, 95% CI: 1.00, 1.06, respectively), but these effect estimates were not robust to adjustment for other pollutants. In single-pollutant models, preconception and first trimester O3 were associated with reduced risk of GDM (OR = 0.94 per 15.7 ppb, 95% CI: 0.92, 0.95; OR = 0.95 per 15.7 ppb, 95% CI: 0.94, 0.97), associations that were robust to adjustment for co-pollutants.ConclusionsMaternal exposure to NO2 during the preconception trimester may increase risk of GDM.

Project description:BackgroundBeing overweight is an important risk factor for Gestational Diabetes Mellitus (GDM), but the underlying mechanisms are not understood. Weight change between pregnancies has been suggested to be an independent mechanism behind GDM. We assessed the risk for GDM in second pregnancy by change in Body Mass Index (BMI) from first to second pregnancy and whether BMI and gestational weight gain modified the risk.Methods and findingsIn this observational cohort, we included 24,198 mothers and their 2 first pregnancies in data from the Medical Birth Registry of Norway (2006-2014). Weight change, defined as prepregnant BMI in second pregnancy minus prepregnant BMI in first pregnancy, was divided into 6 categories by units BMI (kilo/square meter). Relative risk (RR) estimates were obtained by general linear models for the binary family and adjusted for maternal age at second delivery, country of birth, education, smoking in pregnancy, interpregnancy interval, and year of second birth. Analyses were stratified by BMI (first pregnancy) and gestational weight gain (second pregnancy). Compared to women with stable BMI (-1 to 1), women who gained weight between pregnancies had higher risk of GDM-gaining 1 to 2 units: adjusted RR 2.0 (95% CI 1.5 to 2.7), 2 to 4 units: RR 2.6 (2.0 to 3.5), and ≥4 units: RR 5.4 (4.0 to 7.4). Risk increased significantly both for women with BMI below and above 25 at first pregnancy, although it increased more for the former group. A limitation in our study was the limited data on BMI in 2 pregnancies.ConclusionsThe risk of GDM increased with increasing weight gain from first to second pregnancy, and more strongly among women with BMI < 25 in first pregnancy. Our results suggest weight change as a metabolic mechanism behind the increased risk of GDM, thus weight change should be acknowledged as an independent factor for screening GDM in clinical guidelines. Promoting healthy weight from preconception through the postpartum period should be a target.

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Health care for children with diabetes mellitus from low-income families in Ontario and California: a population-based cohort study.

Publications

Health care for children with diabetes mellitus from low-income families in Ontario and California: a population-based cohort study.

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