Category: Nevin Manimala

JMIR Public Health Surveill. 2023 May 30;9:e44647. doi: 10.2196/44647.

ABSTRACT

BACKGROUND: Multimorbidity is characterized by the co-occurrence of 2 or more chronic diseases and has been a focus of the health care sector and health policy makers due to its severe adverse effects.

OBJECTIVE: This paper aims to use the latest 2 decades of national health data in Brazil to analyze the effects of demographic factors and predict the impact of various risk factors on multimorbidity.

METHODS: Data analysis methods include descriptive analysis, logistic regression, and nomogram prediction. The study makes use of a set of national cross-sectional data with a sample size of 877,032. The study used data from 1998, 2003, and 2008 from the Brazilian National Household Sample Survey, and from 2013 and 2019 from the Brazilian National Health Survey. We developed a logistic regression model to assess the influence of risk factors on multimorbidity and predict the influence of the key risk factors in the future, based on the prevalence of multimorbidity in Brazil.

RESULTS: Overall, females were 1.7 times more likely to experience multimorbidity than males (odds ratio [OR] 1.72, 95% CI 1.69-1.74). The prevalence of multimorbidity among unemployed individuals was 1.5 times that of employed individuals (OR 1.51, 95% CI 1.49-1.53). Multimorbidity prevalence increased significantly with age. People over 60 years of age were about 20 times more likely to have multiple chronic diseases than those between 18 and 29 years of age (OR 19.6, 95% CI 19.15-20.07). The prevalence of multimorbidity in illiterate individuals was 1.2 times that in literate ones (OR 1.26, 95% CI 1.24-1.28). The subjective well-being of seniors without multimorbidity was 15 times that among people with multimorbidity (OR 15.29, 95% CI 14.97-15.63). Adults with multimorbidity were more than 1.5 times more likely to be hospitalized than those without (OR 1.53, 95% CI 1.50-1.56) and 1.9 times more likely need medical care (OR 1.94, 95% CI 1.91-1.97). These patterns were similar in all 5 cohort studies and remained stable for over 21 years. A nomogram model was used to predict multimorbidity prevalence under the influence of various risk factors. The prediction results were consistent with the effects of logistic regression; older age and poorer participant well-being had the strongest correlation with multimorbidity.

CONCLUSIONS: Our study shows that multimorbidity prevalence varied little in the past 2 decades but varies widely across social groups. Identifying populations with higher rates of multimorbidity prevalence may improve policy making around multimorbidity prevention and management. The Brazilian government can create public health policies targeting these groups, and provide more medical treatment and health services to support and protect the multimorbidity population.

PMID:37252771 | DOI:10.2196/44647

J Adolesc Young Adult Oncol. 2023 May 26. doi: 10.1089/jayao.2023.0014. Online ahead of print.

ABSTRACT

Purpose: Although adolescent and young adult (AYA) cancer patients are digital natives and have high digital communication needs, previous studies of screening tools for AYAs have primarily used paper when measuring patient-reported outcomes (PROs). There are no reports on using an electronic PRO (ePRO) screening tool with AYAs. This study evaluated the feasibility of such a tool in clinical settings, and assessed the prevalence of AYAs’ distress and supportive care needs. Methods: An ePRO tool based on the Distress Thermometer and Problem List (DTPL)-Japanese (DTPL-J) version for AYAs was implemented in a clinical setting for 3 months. To determine the prevalence of distress and need for supportive care, descriptive statistics were calculated for participant characteristics, selected items, and Distress Thermometer (DT) scores. Response rates, referral rates to an attending physician and other experts, and time required to complete PRO tools were assessed to evaluate feasibility. Results: From February to April 2022, 244 (93.8%) of 260 AYAs completed the ePRO tool based on the DTPL-J for AYAs. Based on a DT cutoff of ≥5, 65 of 244 patients (26.6%) had high distress. Worry (n = 81, 33.2%) was the most frequently selected item. Primary nurses referred 85 (32.7%) patients to an attending physician or other experts. The referral rate resulting from ePRO screening was significantly higher than that after PRO screening (χ²(1) = 17.99, p < 0.001). The average response time did not differ significantly between ePRO and PRO screening (p = 0.252). Conclusion: This study suggests the feasibility of an ePRO tool based on the DTPL-J for AYAs.

PMID:37252764 | DOI:10.1089/jayao.2023.0014

J Correct Health Care. 2023 May 26. doi: 10.1089/jchc.22.03.0023. Online ahead of print.

ABSTRACT

The aim of this study was to assess the availability of medications for opioid use disorder (MOUD) and other services for pregnant people in jails in counties heavily impacted by opioid overdose in the United States. Counties were selected based on absolute number and population rate of opioid-overdose fatalities. Structured interviews were completed with representatives from 174 jails that house pregnant women. Descriptive statistics examine MOUD availability and differences in service provision and community-level characteristics based on MOUD availability. Most jails in the study sample (84.5%) had MOUD available for pregnant people; however, less than half of these jails ensured continuity of care. Jails without MOUD available are more likely to provide non-MOUD substance use services. These jails are more often located in smaller, rural counties in the Midwest and have higher rates of White residents and lower rates of Hispanic and African American residents. Gaps in MOUD availability in jails and continuity of care violate medical guidelines for treatment of pregnant patients with opioid use disorder and increase their risk of overdose. In addition, there are disparities across communities in access to MOUD for pregnant people in jails.

PMID:37252747 | DOI:10.1089/jchc.22.03.0023

JAMA Pediatr. 2023 May 30. doi: 10.1001/jamapediatrics.2023.1379. Online ahead of print.

ABSTRACT

IMPORTANCE: Although inequitable care due to racism and bias is well documented in health care, the impact on health care-associated infections is less understood.

OBJECTIVE: To determine whether disparities in first central catheter-associated bloodstream infection (CLABSI) rates existed for pediatric patients of minoritized racial, ethnic, and language groups and to evaluate the outcomes associated with quality improvement initiatives for addressing these disparities.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study retrospectively examined outcomes of 8269 hospitalized patients with central catheters from October 1, 2012, to September 30, 2019, at a freestanding quaternary care children’s hospital. Subsequent quality improvement interventions and follow-up were studied, excluding catheter days occurring after the outcome and episodes with catheters of indeterminate age through September 2022.

EXPOSURES: Patient self-reported (or parent/guardian-reported) race, ethnicity, and language for care as collected for hospital demographic purposes.

MAIN OUTCOMES AND MEASURES: Central catheter-associated bloodstream infection events identified by infection prevention surveillance according to National Healthcare Safety Network criteria were reported as events per 1000 central catheter days. Cox proportional hazards regression was used to analyze patient and central catheter characteristics, and interrupted time series was used to analyze quality improvement outcomes.

RESULTS: Unadjusted infection rates were higher for Black patients (2.8 per 1000 central catheter days) and patients who spoke a language other than English (LOE; 2.1 per 1000 central catheter days) compared with the overall population (1.5 per 1000 central catheter days). Proportional hazard regression included 225 674 catheter days with 316 infections and represented 8269 patients. A total of 282 patients (3.4%) experienced a CLABSI (mean [IQR] age, 1.34 [0.07-8.83] years; female, 122 [43.3%]; male, 160 [56.7%]; English-speaking, 236 [83.7%]; LOE, 46 [16.3%]; American Indian or Alaska Native, 3 [1.1%]; Asian, 14 [5.0%]; Black, 26 [9.2%]; Hispanic, 61 [21.6%]; Native Hawaiian or Other Pacific Islander, 4 [1.4%]; White, 139 [49.3%]; ≥2 races, 14 [5.0%]; unknown race and ethnicity or refused to answer, 15 [5.3%]). In the adjusted model, a higher hazard ratio (HR) was observed for Black patients (adjusted HR, 1.8; 95% CI, 1.2-2.6; P = .002) and patients who spoke an LOE (adjusted HR, 1.6; 95% CI, 1.1-2.3; P = .01). Following quality improvement interventions, infection rates in both subgroups showed statistically significant level changes (Black patients: -1.77; 95% CI, -3.39 to -0.15; patients speaking an LOE: -1.25; 95% CI, -2.23 to -0.27).

CONCLUSIONS AND RELEVANCE: The study’s findings show disparities in CLABSI rates for Black patients and patients who speak an LOE that persisted after adjusting for known risk factors, suggesting that systemic racism and bias may play a role in inequitable hospital care for hospital-acquired infections. Stratifying outcomes to assess for disparities prior to quality improvement efforts may inform targeted interventions to improve equity.

PMID:37252746 | DOI:10.1001/jamapediatrics.2023.1379

Health Promot J Austr. 2023 May 30. doi: 10.1002/hpja.753. Online ahead of print.

ABSTRACT

ISSUE ADDRESSED: Pakistani migrants are one of the fastest-growing culturally and linguistically diverse (CALD) communities in Australia, but there is currently a lack of information regarding their health literacy. This study aimed to investigate the health literacy of Pakistani migrants residing in Australia.

METHODS: Using a cross-sectional study design, health literacy was measured using the Urdu version of Health Literacy Questionnaire (HLQ). Descriptive statistics and linear regression were used to describe the health literacy profile of respondents and to examine its association with their demographic characteristics.

RESULTS: The responses of 202 Pakistani migrants were included. The median age of the respondents was 36 years, 61.8% were males and 87.6% had a university education. The majority spoke Urdu at home and almost 80% were Australian permanent residents or citizens. Pakistani respondents scored high on HLQ domains; feeling understood by health providers (Scale 1), social support for health care (Scales 4), engaging with health care providers (Scale 6) and understanding health information (Scale 9). The respondents scored low on HLQ domains; having sufficient information (Scale 2), actively managing health (Scale 3), appraisal of health information (Scale 5), navigating the health care system (Scale 7) and ability to find information (Scale 8). In the regression model, university education and age were significantly associated with health literacy in almost all the domains, but the effect size was small for age. Speaking English at home and being a permanent resident were also associated with better health literacy in two to three HLQ domains.

CONCLUSIONS: Health literacy strengths and weaknesses of Pakistani migrants residing in Australia were identified. Health care providers and organisations may use these findings to tailor health information and services to better support health literacy in this community. SO WHAT?: This study will inform future interventions to better support health literacy and reduce health disparities in Pakistani migrants residing in Australia.

PMID:37252730 | DOI:10.1002/hpja.753

JAMA Intern Med. 2023 May 30. doi: 10.1001/jamainternmed.2023.1964. Online ahead of print.

ABSTRACT

IMPORTANCE: Health-related social needs are increasingly being screened for in primary care practices, but it remains unclear how much additional financing is required to address those needs to improve health outcomes.

OBJECTIVE: To estimate the cost of implementing evidence-based interventions to address social needs identified in primary care practices.

DESIGN, SETTING, AND PARTICIPANTS: A decision analytical microsimulation of patients seen in primary care practices, using data on social needs from the National Center for Health Statistics from 2015 through 2018 (N = 19 225) was conducted. Primary care practices were categorized as federally qualified health centers (FQHCs), non-FQHC urban practices in high-poverty areas, non-FQHC rural practices in high-poverty areas, and practices in lower-poverty areas. Data analysis was performed from March 3 to December 16, 2022.

INTERVENTION: Simulated evidence-based interventions of primary care-based screening and referral protocols, food assistance, housing programs, nonemergency medical transportation, and community-based care coordination.

MAIN OUTCOMES AND MEASURES: The primary outcome was per-person per-month cost of interventions. Intervention costs that have existing federally funded financing mechanisms (eg, the Supplemental Nutrition Assistance Program) and costs without such an existing mechanism were tabulated.

RESULTS: Of the population included in the analysis, the mean (SD) age was 34.4 (25.9) years, and 54.3% were female. Among people with food and housing needs, most were program eligible for federally funded programs, but had low enrollment (eg, due to inadequate program capacity), with 78.0% of people with housing needs being program eligible vs 24.0% enrolled, and 95.6% of people with food needs being program eligible vs 70.2% enrolled. Among those with transportation insecurity and care coordination needs, eligibility criteria limited enrollment (26.3% of those in need being program eligible for transportation programs, and 5.7% of those in need being program eligible for care coordination programs). The cost of providing evidence-based interventions for these 4 domains averaged $60 (95% CI, $55-$65) per member per month (including approximately $5 for screening and referral management in clinics), of which $27 (95% CI, $24-$31) (45.8%) was federally funded. While disproportionate funding was available to populations seen at FQHCs, populations seen at non-FQHC practices in high-poverty areas had larger funding gaps (intervention costs not borne by existing federal funding mechanisms).

CONCLUSIONS AND RELEVANCE: In this decision analytical microsimulation study, food and housing interventions were limited by low enrollment among eligible people, whereas transportation and care coordination interventions were more limited by narrow eligibility criteria. Screening and referral management in primary care was a small expenditure relative to the cost of interventions to address social needs, and just under half of the costs of interventions were covered by existing federal funding mechanisms. These findings suggest that many resources are necessary to address social needs that fall largely outside of existing federal financing mechanisms.

PMID:37252714 | DOI:10.1001/jamainternmed.2023.1964

Arch Endocrinol Metab. 2023 May 12;67(4):e000621. doi: 10.20945/2359-3997000000621.

ABSTRACT

OBJECTIVE: The effects of the COVID-19 pandemic on the control of diabetes mellitus in patients are largely unknown. In this study we aimed to analyze the impact of the pandemic and the ensuing lockdown on the management of type 2 diabetes mellitus.

SUBJECTS AND METHODS: A total of 7,321patients with type 2 diabetes mellitus (4,501 from the pre-pandemic period, 2,820 from the post-pandemic period) were studied retrospectively.

RESULTS: The admission of patients with diabetes melitus (DM) decreased significantly during the pandemic (4,501 pre-pandemic vs. 2,820 post-pandemic; p < 0.001). The mean age of patients was statistically lower (51.5 ± 14.0 vs. 49.7 ± 14.5 years; p < 0.001), and the mean glycated hemoglobin (A1c) level was significantly higher (7.9% ± 2.4% vs. 7.3% ± 1.7%; p < 0.001) in the post-pandemic period than in the pre-pandemic. The female/male ratio was similar in both periods (59.9%/40.1% for pre-pandemic, 58.6%/41.4% for post-pandemic; p = 0.304). As calculated by month the pre-pandemic rate of women was higher only in January (53.1% vs. 60.6%, p = 0.02). Mean A1c levels were higher in the postpandemic period than in the same month of the previous year, excluding July and October (p = 0.001 for November, p < 0.001 for others). Postpandemic patients admitted to the outpatient clinic were significantly younger than prepandemic visits for July (p = 0.001), August (p < 0.001) and December (p < 0.001).

CONCLUSION: The lockdown had detrimental effects on blood sugar management in patients with DM. Hence, diet and exercise programs should be adapted to home conditions, and social and psychological support should be provided to patients with DM.

PMID:37252703 | DOI:10.20945/2359-3997000000621

Arch Endocrinol Metab. 2023 May 12;67(4):e000609. doi: 10.20945/2359-3997000000609.

ABSTRACT

OBJECTIVE: A common problem with antithyroid drugs (ATD) treatment in patients with Graves’ disease (GD) is the high recurrence rate after drug withdrawal. Identifying risk factors for recurrence is crucial in clinical practice. We hereby prospectively analyze risk factors for the recurrence of GD in patients treated with ATD in southern China.

SUBJECTS AND METHODS: Patients who were newly diagnosed with GD and aged > 18 years were treated with ATD for 18 months and followed up for 1 year after ATD withdrawal. Recurrence of GD during follow-up was assessed. All data were analyzed by Cox regression with P values < 0.05 considered statistically significant.

RESULTS: A total of 127 Graves’ hyperthyroidism patients were included. During an average follow-up of 25.7 (standard deviation = 8.7) months, 55 (43%) had a recurrence within 1 year after withdraw of anti-thyroid drugs. After adjustment for potential confounding factors, the significant association remained for the presence of insomnia (hazard ratio (HR) 2.94, 95% confidence interval (CI) 1.47-5.88), greater goiter size (HR 3.34, 95% CI 1.11-10.07), higher thyrotrophin receptor antibody (TRAb) titer (HR 2.66, 95% CI 1.12-6.31) and a higher maintenance dose of methimazole (MMI) (HR 2.14, 95% CI 1.14-4.00).

CONCLUSION: Besides conventional risk factors (i.e., goiter size, TRAb and maintenance MMI dose) for recurrent GD after ATD withdraw, insomnia was associated with a 3-fold risk of recurrence. Further clinical trials investigating the beneficial effect of improving sleep quality on prognosis of GD are warranted.

PMID:37252698 | DOI:10.20945/2359-3997000000609

Arch Endocrinol Metab. 2023 May 12;67(4):e000605. doi: 10.20945/2359-3997000000605.

ABSTRACT

OBJECTIVE: Evaluate the influence of isolated and associated prepregnancy obesity and gestational diabetes mellitus (GDM) on adverse perinatal outcomes.

MATERIALS AND METHODS: Cross-sectional observational study with women who delivered at a Brazilian Maternity Hospital, between August and December 2020. Data were collected by interview with application form, and medical records. Sample was stratified by body mass index (BMI) and GDM screening in four groups: no obesity (BMI < 30 kg/m²) no GDM – reference; isolated GDM; isolated obesity (BMI ≥ 30 kg/m²); and obesity with GDM. Preeclampsia (PE), cesarean section (CS), large-for-gestational-age (LGA) newborn and admission to neonatal intensive care unit (NICU) were analyzed by odds ratio (OR) adjusted for confounding factors, adopting 95% confidence interval (CI) and P < 0.05 statistically significant.

RESULTS: From 1,618 participants, isolated obesity group (233/14.40%) had high chance of PE (OR = 2.16; CI: 1.364-3.426; P = 0.001), isolated GDM group (190/11.74%) had high chance of CS (OR = 1.736; CI: 1.136-2.652; P = 0.011) and NICU admission (OR = 2.32; CI: 1.265-4.261; P = 0.007), and obesity with GDM group (121/7.48%) had high chance of PE (OR = 1.93; CI: 1.074-3.484; P = 0.028), CS (OR = 1.925; CI: 1.124-3.298; P = 0.017) and LGA newborn (OR = 1.81; CI: 1.027-3.204; P = 0.040), compared with reference (1,074/66.38%).

CONCLUSION: Obesity and GDM enhances the chance of different negative outcomes, worsening this prognosis when associated.

PMID:37252694 | DOI:10.20945/2359-3997000000605

J R Stat Soc Ser C Appl Stat. 2020 Aug 13;69(5):1269-1283. doi: 10.1111/rssc.12435. eCollection 2020 Nov.

ABSTRACT

When testing for a rare disease, prevalence estimates can be highly sensitive to uncertainty in the specificity and sensitivity of the test. Bayesian inference is a natural way to propagate these uncertainties, with hierarchical modelling capturing variation in these parameters across experiments. Another concern is the people in the sample not being representative of the general population. Statistical adjustment cannot without strong assumptions correct for selection bias in an opt-in sample, but multilevel regression and post-stratification can at least adjust for known differences between the sample and the population. We demonstrate hierarchical regression and post-stratification models with code in Stan and discuss their application to a controversial recent study of SARS-CoV-2 antibodies in a sample of people from the Stanford University area. Wide posterior intervals make it impossible to evaluate the quantitative claims of that study regarding the number of unreported infections. For future studies, the methods described here should facilitate more accurate estimates of disease prevalence from imperfect tests performed on non-representative samples.

PMID:37252679 | PMC:PMC10016948 | DOI:10.1111/rssc.12435