Prevalence Trends of Diabetes Subgroups in the United States: A Data-driven Analysis Spanning Three Decades From NHANES (1988-2018)

Diabetes Disparities in the United States: Trends by Educational Attainment from 2001 to 2020

INTRODUCTION

Tracking changes in socioeconomic disparities in diabetes in the U.S. is important to evaluate progress in health equity and guide prevention efforts. Disparities in diabetes prevalence by educational attainment from 2001 to 2020 were investigated.

METHODS

Using a serial cross-sectional design, data from 33,220 adults aged 30-79 assessed in nine rounds of the National Health and Nutrition Examination Surveys between 2001 and 2020 were analyzed in 2023-2024. Diabetes was defined as self-reported prior diagnosis, elevated glycated hemoglobin (HbA1c≥6.5%), or use of diabetes medications. Marginalized age- and covariate-adjusted prevalence differences (PD) and prevalence ratios (PR) of diabetes by educational attainment (less than high school graduation, high school graduation, some college education or associate degree, or college graduation [reference]) by calendar period (2001-2004, 2005-2008, 2009-2012, 2013-2016, 2017-2020) were derived from logistic regression models.

RESULTS

From 2001 to 2020, age-adjusted diabetes prevalence was consistently higher among adults without a college degree. Adults without a high school diploma exhibited the largest disparities in both 2001-2004 (PD 8.0%; 95%CI 5.6-10.5 and PR 2.1; 95%CI 1.5-2.6) and 2017-20 (PD 11.0%; 95%CI 6.7-15.2 and PR 2.1; 95%CI 1.5-2.7). Between 2001-2004 and 2017-2020, the absolute disparity in diabetes changed only among adults with a high school diploma (increase from PD 1.7%; 95%CI -0.5- 3.9 to PD 8.8% 95%CI 4.1-13.4, respectively), while the PR did not change in any group. Education-related disparities in diabetes were attenuated after accounting for socio-demographic factors and BMI.

CONCLUSIONS

From 2001 to 2020, national education-related disparities in diabetes prevalence have shown no signs of narrowing.

Associations between hearing loss, peripheral neuropathy, balance, and survival in older primary care patients

BACKGROUND

Both age-associated hearing loss (AAHL) and peripheral neuropathy (PN) are common in older patients, and both are associated with impaired balance, falls, and premature mortality. The objectives of this study were to document the prevalence and severity of AAHL in older primary care patients, and to explore associations between AAHL, PN, balance, falls, and mortality.

METHODS

We analyzed information obtained in 1999 from 793 primary care patients recruited from practices participating in the Oklahoma Longitudinal Assessment of the Health Outcomes of Mature Adults (OKLAHOMA) Studies. Available data included demographic and health information, history of falls and hospitalizations, audiometry, balance testing, examination of the peripheral nerves, 50 foot timed gait, and dates of death up to 22 calendar years and 8106 person-years of follow-up. Proportionate hazards (PH) and structural equation modeling (SEM) were used to examine associations between AAHL, PN, balance, gait time, and mortality.

RESULTS

501 of the 793 participants (63%) had AAHL. Another 156 (20%) had low frequency and 32 (4%) had unilateral deficits. Those with moderate or severe AAHL and the 255 (32%) with PN had impaired balance (p < 0.0001), increased gait time (p = 0.0001), and reduced survival time (p < 0.0001). In the PH model, both AAHL and PN were associated with earlier mortality (H.Rs. [95% C.I.]: 1.36 [1.13-1.64] and 1.32 [1.10-1.59] respectively). The combination of moderate or severe AAHL and PN, present in 24% of participants, predicted earlier mortality than predicted by either deficit alone (O.R. [95% C.I.I] 1.55 [1.25-1.92]). In the SEM models, the impacts of both moderate or severe AAHL and PN on survival were mediated, in part, through loss of balance.

CONCLUSIONS

Hearing loss and PN, both common in older patients, appear to be independently and additively associated with premature mortality. Those associations may be mediated in part by impaired balance. The Mechanisms are likely multiple and complex.

Metformin's role in lowering colorectal cancer risk among individuals with diabetes from the Southern Community Cohort Study

BACKGROUND

Metformin, utilized to manage hyperglycemia, has been linked to a reduced risk of colorectal cancer (CRC) among individuals with diabetes. However, evidence is lacking for non-Hispanic Black individuals and those with lower socioeconomic status (SES), who face elevated risk for both diabetes and CRC. In this study, we investigated the association between metformin use and incident CRC risk within the Southern Community Cohort Study (SCCS), a racially- and SES-diverse prospective cohort.

METHODS

Participants reported their diabetes diagnosis and medications, including metformin, upon enrollment (2002-2009) and during follow-up surveys approximately every five years. Incident cases of CRC were identified through state cancer registries and the National Death Index. Proportional hazards models were employed to explore the relationship between metformin use and CRC risk, adjusted for cancer risk factors.

RESULTS

A total of 25,992 participants with diabetes were included in the analysis, among whom 10,095 were taking metformin. Of these participants, 76% identified as non-Hispanic Black, and 60% reported household incomes <$15,000/year. Metformin use was associated with a significantly lower CRC risk (HR [95% CI]: 0.71 [0.55-0.93]), with consistent results for both colon (0.80 [0.59-1.07]) and rectal cancers (0.49 [0.28-0.86]). The protective association appeared to be stronger among non-Hispanic White individuals (0.51 [0.31-0.85]) compared to non-Hispanic Black participants (0.80 [0.59-1.08], p-interaction =.13). Additionally, a protective association was observed among obese individuals (BMI ≥30 kg/m2, 0.59 [0.43-0.82] but not among non-obese participants (0.99 [0.65-1.51], p-interaction =.05) CONCLUSION: Our findings indicate that metformin use is associated with a reduced risk of CRC in individuals with diabetes, including among those from predominantly low SES backgrounds. These results support previous epidemiological findings, and demonstrate that the protective association for metformin in relation to incident CRC likely generalizes to populations with higher underlying risk.

Trends and Disparities in Treatment and Control of Atherosclerotic Cardiovascular Disease in US Adults, 1999 to 2018

BACKGROUND

Although cardiovascular mortality continued declining from 2000 to 2019, the rate of this decrease decelerated. We aimed to assess the trends and disparities in risk factor control and treatment among US adults with atherosclerotic cardiovascular disease to find potential causes of the deceleration.

METHODS AND RESULTS

A total of 55 ,021 participants, aged ≥20 years, from the 1999 to 2018 National Health and Nutrition Examination Survey were included, of which 5717 were with atherosclerotic cardiovascular disease. Risk factor control was defined as hemoglobin A1c <7%, blood pressure <140/90 mm Hg, and non-high-density lipoprotein cholesterol <100 mg/dL. The prevalence of atherosclerotic cardiovascular disease oscillated between 7.3% and 8.9% from 1999 to 2018. A significant increasing trend was observed in the prevalence of diabetes, obesity, heavy alcohol consumption, and self-reported hypertension within the population with atherosclerotic cardiovascular disease (Ptrend≤0.001). Non-high-density lipoprotein cholesterol <100 mg/dL increased from 7.1% in 1999 to 2002 to 15.7% in 2003 to 2006, before plateauing. Blood pressure control (<140/90 mm Hg) increased until 2011 to 2014, but declined to 70.1% in 2015 to 2018 (Ptrend<0.001, Pjoinpoint=0.14). Similarly, the proportion of participants achieving hemoglobin A1c control began to decrease after 2006 (Pjoinpoint=0.05, Ptrend=0.001). The percentage of participants achieving all 3 targets increased significantly from 4.5% to 18.6% across 1999 to 2018 (Ptrend=0.02), but the increasing trend decelerated after 2005 to 2006 (Pjoinpoint<0.001). Striking disparities in risk factor control and medication use persisted between sexes, and between different racial and ethnic populations.

CONCLUSIONS

Worsened control of glycemia, blood pressure, obesity, and alcohol consumption, leveled lipid control, and persistent socioeconomic disparities may be contributing factors to the observed deceleration in decreasing cardiovascular mortality trends.

Diabetes subgroups and sociodemographic inequalities in Mexico: a cross-sectional analysis of nationally representative surveys from 2016 to 2022

Background

Differences in the prevalence of four diabetes subgroups have been reported in Mexico compared to other populations, but factors that may contribute to these differences are poorly understood. Here, we estimate the prevalence of diabetes subgroups in Mexico and evaluate their correlates with indicators of social disadvantage using data from national representative surveys.

Methods

We analyzed serial, cross-sectional Mexican National Health and Nutrition Surveys spanning 2016, 2018, 2020, 2021, and 2022, including 23,354 adults (>20 years). Diabetes subgroups (obesity-related [MOD], severe insulin-deficient [SIDD], severe insulin-resistant [SIRD], and age-related [MARD]) were classified using self-normalizing neural networks based on a previously validated algorithm. We used the density-independent social lag index (DISLI) as a proxy of state-level social disadvantage.

Findings

We identified 4204 adults (median age: 57, IQR: 47-66, women: 64%) living with diabetes, yielding a pooled prevalence of 16.04% [95% CI: 14.92-17.17]. When stratified by diabetes subgroup, prevalence was 6.62% (5.69-7.55) for SIDD, 5.25% (4.52-5.97) for MOD, 2.39% (1.95-2.83) for MARD, and 1.27% (1.00-1.54) for SIRD. SIDD and MOD clustered in Southern Mexico, whereas MARD and SIRD clustered in Northern Mexico and Mexico City. Each standard deviation increase in DISLI was associated with higher odds of SIDD (OR: 1.12, 95% CI: 1.06-1.12) and lower odds of MOD (OR: 0.93, 0.88-0.99). Speaking an indigenous language was associated with higher odds of SIDD (OR: 1.35, 1.16-1.57) and lower odds of MARD (OR 0.58, 0.45-0.74).

Interpretation

Diabetes prevalence in Mexico is rising in the context of regional and sociodemographic inequalities across distinct diabetes subgroups. SIDD is a subgroup of concern that may be associated with inadequate diabetes management, mainly in marginalized states.

Funding

This research was supported by Instituto Nacional de Geriatría in Mexico.

Changes in the Prevalence, Incidence, and Disability-Adjusted Life Years of Non-alcoholic Fatty Liver Disease in the United States Between 1990 and 2019

INTRODUCTION

This study aimed to determine trends in the prevalence, incidence, and disability-adjusted life years (DALYs) of Non-alcoholic Fatty Liver Disease (NAFLD) in the US across different states and age groups between 1990 and 2019.

METHODS

Using the Global Burden of Disease database, this study analyzed the prevalence, incidence, and DALYs of NAFLD in the US between 1990 and 2019. We computed relative percentage changes, performed Joinpoint regression analyses of trends, and compared these between states and age groups (5-19, 20-55, and more than 55 years old).

RESULTS

In the United States, the prevalence of NAFLD increased more than the global average over the study period (+ 30.7% vs. + 24.5%), especially in the 5-19-year-old age group. Among all states, Kansas, Washington, and California had the highest increase in prevalence and the District of Columbia followed by Massachusetts and North Carolina had the lowest increase in prevalence. The increase in incidence was greater in the US than the global average (+ 37.18% vs. + 7.28%). West Virginia, Ohio, and Kentucky had the highest increase in incidence. The increase in DALYs was greater in the US compared to the global average (+ 57.15% vs. + 12.65%). Alaska, West Virginia, and Kentucky had the highest increase in DALYs. The increased incidence and DALYs were found in all states except in the District of Columbia.

CONCLUSION

The prevalence of NAFLD in the US has increased more rapidly than the global average, especially in the pediatric population. South and Midwest states have the highest increase in prevalence, incidence, and DALYs of NAFLD. The District of Columbia was the only state that has decreased incidence and DALYs.

National population-based estimates for major birth defects, 2016-2020

BACKGROUND

We provide updated crude and adjusted prevalence estimates of major birth defects in the United States for the period 2016-2020.

METHODS

Data were collected from 13 US population-based surveillance programs that used active or a combination of active and passive case ascertainment methods to collect all birth outcomes. These data were used to calculate pooled prevalence estimates and national prevalence estimates adjusted for maternal race/ethnicity for all conditions, and maternal age for trisomies and gastroschisis. Prevalence was compared to previously published national estimates from 1999 to 2014.

RESULTS

Adjusted national prevalence estimates per 10,000 live births ranged from 0.63 for common truncus to 18.65 for clubfoot. Temporal changes were observed for several birth defects, including increases in the prevalence of atrioventricular septal defect, tetralogy of Fallot, omphalocele, trisomy 18, and trisomy 21 (Down syndrome) and decreases in the prevalence of anencephaly, common truncus, transposition of the great arteries, and cleft lip with and without cleft palate.

CONCLUSION

This study provides updated national estimates of selected major birth defects in the United States. These data can be used for continued temporal monitoring of birth defects prevalence. Increases and decreases in prevalence since 1999 observed in this study warrant further investigation.

Cardiometabolic and renal phenotypes and transitions in the United States population

Cardiovascular and renal conditions have both shared and distinct determinants. In this study, we applied unsupervised clustering to multiple rounds of the National Health and Nutrition Examination Survey from 1988 to 2018, and identified 10 cardiometabolic and renal phenotypes. These included a 'low risk' phenotype; two groups with average risk factor levels but different heights; one group with low body-mass index and high levels of high-density lipoprotein cholesterol; five phenotypes with high levels of one or two related risk factors ('high heart rate', 'high cholesterol', 'high blood pressure', 'severe obesity' and 'severe hyperglycemia'); and one phenotype with low diastolic blood pressure (DBP) and low estimated glomerular filtration rate (eGFR). Prevalence of the 'high blood pressure' and 'high cholesterol' phenotypes decreased over time, contrasted by a rise in the 'severe obesity' and 'low DBP, low eGFR' phenotypes. The cardiometabolic and renal traits of the US population have shifted from phenotypes with high blood pressure and cholesterol toward poor kidney function, hyperglycemia and severe obesity.

Associations between avocado intake and measures of glucose and insulin homeostasis in Hispanic individuals with and without type 2 diabetes: Results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

BACKGROUND AND AIMS

To investigate associations between avocado intake and glycemia in adults with Hispanic/Latino ancestry.

METHODS AND RESULTS

The associations of avocado intake with measures of insulin and glucose homeostasis were evaluated in a cross-sectional analysis of up to 14,591 Hispanic/Latino adults, using measures of: average glucose levels (hemoglobin A1c; HbA1c), fasting glucose and insulin, glucose and insulin levels after an oral glucose tolerance test (OGTT), and calculated measures of insulin resistance (HOMA-IR, and HOMA-%β), and insulinogenic index. Associations were assessed using multivariable linear regression models, which controlled for sociodemographic factors and health behaviors, and which were stratified by dysglycemia status. In those with normoglycemia, avocado intake was associated with a higher insulinogenic index (β = 0.17 ± 0.07, P = 0.02). In those with T2D (treated and untreated), avocado intake was associated with lower hemoglobin A1c (HbA1c; β = -0.36 ± 0.21, P = 0.02), and lower fasting glucose (β = -0.27 ± 0.12, P = 0.02). In the those with untreated T2D, avocado intake was additionally associated with HOMA-%β (β = 0.39 ± 0.19, P = 0.04), higher insulin values 2-h after an oral glucose load (β = 0.62 ± 0.23, P = 0.01), and a higher insulinogenic index (β = 0.42 ± 0.18, P = 0.02). No associations were observed in participants with prediabetes.

CONCLUSIONS

We observed an association of avocado intake with better glucose/insulin homeostasis, especially in those with T2D.

Trends in weight change patterns across life course among US adults, 1988-2018: population-based study

BACKGROUND

To examine trends in weight change patterns from young adulthood through midlife to late adulthood and their sex and racial/ethnic disparities among US adults from 1988 to 2018.

METHODS

A total of 48,969 participants from the National Health and Nutrition Examination Survey 1988-1994 and 2001-2018 were included.

RESULTS

The age-adjusted prevalence of stable non-obesity between young adulthood and midlife declined significantly from 84.1% (95 CI, 82.9-85.3%) in 1988-1994 to 68.7% (67.1-70.2%) in 2013-2018, and between midlife and late adulthood from 71.2% (69.2-73.1%) to 52.4% (50.5-54.2%). The magnitude of increase in the prevalence of weight gain from young adulthood to midlife (from 10.8% [9.9-11.6%] in 1988-1994 to 21.2% [20-22.3%] in 2013-2018; P < 0.001 for trend) was greater than that from midlife to late adulthood (from 14.1% [12.9-15.3%] to 17.2% [16.2-18.1%]; P = 0.002 for trend). The magnitude of increase in the prevalence of stable obesity from young adulthood to midlife (from 3.9% [3.1-4.8%] in 1988-1994 to 9.2% [8.2-10.3%] in 2013-2018; P < 0.001 for trend) was smaller than that from midlife to late adulthood (from 11.2% [10.1-12.2%] to 24.8% [23.3-26.3%]; P < 0.001 for trend). The declining trends in the prevalence of stable non-obesity and increasing trends in the prevalence of weight gain and stable obesity from young adulthood through midlife to late adulthood were also observed for all sex and race/ethnicity subgroups. The magnitude of decrease in the prevalence of stable non-obesity, and the magnitude of increase in the prevalence of weight gain from young adulthood through midlife to late adulthood were greater in men than in women (all P for interaction < 0.01). Weight gain patterns for those aged ≥ 65 years were substantially different from the younger age groups.

CONCLUSIONS

More young people born in later years are encountering obesity and accumulate greater obesity exposure across their lives than young people born in earlier years.

Precision subclassification of type 2 diabetes: a systematic review

BACKGROUND

Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients.

METHODS

We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches.

RESULTS

Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes.

CONCLUSION

Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.

Machine learning based study for the classification of Type 2 diabetes mellitus subtypes

PURPOSE

Data-driven diabetes research has increased its interest in exploring the heterogeneity of the disease, aiming to support in the development of more specific prognoses and treatments within the so-called precision medicine. Recently, one of these studies found five diabetes subgroups with varying risks of complications and treatment responses. Here, we tackle the development and assessment of different models for classifying Type 2 Diabetes (T2DM) subtypes through machine learning approaches, with the aim of providing a performance comparison and new insights on the matter.

METHODS

We developed a three-stage methodology starting with the preprocessing of public databases NHANES (USA) and ENSANUT (Mexico) to construct a dataset with N = 10,077 adult diabetes patient records. We used N = 2,768 records for training/validation of models and left the remaining (N = 7,309) for testing. In the second stage, groups of observations -each one representing a T2DM subtype- were identified. We tested different clustering techniques and strategies and validated them by using internal and external clustering indices; obtaining two annotated datasets Dset A and Dset B. In the third stage, we developed different classification models assaying four algorithms, seven input-data schemes, and two validation settings on each annotated dataset. We also tested the obtained models using a majority-vote approach for classifying unseen patient records in the hold-out dataset.

RESULTS

From the independently obtained bootstrap validation for Dset A and Dset B, mean accuracies across all seven data schemes were [Formula: see text] ([Formula: see text]) and [Formula: see text] ([Formula: see text]), respectively. Best accuracies were [Formula: see text] and [Formula: see text]. Both validation setting results were consistent. For the hold-out dataset, results were consonant with most of those obtained in the literature in terms of class proportions.

CONCLUSION

The development of machine learning systems for the classification of diabetes subtypes constitutes an important task to support physicians for fast and timely decision-making. We expect to deploy this methodology in a data analysis platform to conduct studies for identifying T2DM subtypes in patient records from hospitals.

Systematic review of precision subclassification of type 2 diabetes

Heterogeneity in type 2 diabetes presentation, progression and treatment has the potential for precision medicine interventions that can enhance care and outcomes for affected individuals. We undertook a systematic review to ascertain whether strategies to subclassify type 2 diabetes are associated with improved clinical outcomes, show reproducibility and have high quality evidence. We reviewed publications that deployed 'simple subclassification' using clinical features, biomarkers, imaging or other routinely available parameters or 'complex subclassification' approaches that used machine learning and/or genomic data. We found that simple stratification approaches, for example, stratification based on age, body mass index or lipid profiles, had been widely used, but no strategy had been replicated and many lacked association with meaningful outcomes. Complex stratification using clustering of simple clinical data with and without genetic data did show reproducible subtypes of diabetes that had been associated with outcomes such as cardiovascular disease and/or mortality. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into meaningful groups. More studies are needed to test these subclassifications in more diverse ancestries and prove that they are amenable to interventions.

Prevalence of diabetes in the USA from the perspective of demographic characteristics, physical indicators and living habits based on NHANES 2009-2018

Objective

To determine differences in DM in the U.S. population according to demographic characteristics, physical indicators and living habits.

Methods

23 546 participants in the 2009 to 2018 National Health and Nutrition Examination Survey (NHANES) who were 20 year of age or older and not pregnant. All analyses used weighted samples and considered the stratification and clustering of the design. Specific indicators include length of leg (cm), BMI (kg/cm2), TCHOL (mg/dL), fasting plasma glucose (mg/dL) and comparison of means and the proportion of participants with DM.

Results

The prevalence of DM in the USA has been rising modestly in the past decade, and were consistent and robust for the observed differences in age, sex, and ethnicity. Compared with white participants, black participants and Mexican-American were both more likely (P<0.001) to have diabetes: 14.6% (CI, 13.6% to 15.6%) among black participants, 10.6% (CI, 9.9% to 11.3%) among white participants, and 13.5% (CI, 11.9% to 15.2%) among Mexican-American participants. The prevalence of diabetes is increasing with age, males peaked around the 60s, and women around the 70s. The overall mean leg length and TCHOL was lower in diabetics than in non-diabetics (1.07 cm, 18.67 mg/dL, respectively), while mean BMI were higher in diabetics than in non-diabetics (4.27 kg/cm2). DM had the greatest effect on decline of TCHOL in white participants (23.6 mg/dL), less of an effect in black participants (9.67 mg/dL), and the least effect in Mexican-American participants (8.25 mg/dL). Notably, smoking had great effect on percent increment of DM in whites (0.2%), and have little effect on black and Mexican-Americans.

Conclusions

DM is more common in the general population than might be clinically recognized, and the prevalence of DM was associated to varying degrees with many indicators of demographic characteristics, physical indicators, and living habits. These indicators should be linked with medical resource allocation and scientific treatment methods to comprehensively implement the treatment of DM.

Ankle Fractures in Diabetic Patients: A Critical Analysis

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Patients with diabetes are at higher risk for complications after surgical fixation of unstable fractures due to impaired neurovascular functioning and wound-healing capabilities.

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Patients with uncontrolled diabetes have higher rates of complications when compared with patients with controlled diabetes.

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Despite higher rates of complications, operative fixation of unstable ankle fractures in diabetic patients reliably leads to a functional lower extremity with an overall lower rate of complications than nonoperative management.

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Operatively and nonoperatively managed ankle fractures in patients with diabetes should remain non-weight-bearing for an extended period of time.

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Discussion of risk of poor outcomes including deep infection, loss of reduction, return to the operating room, and risk of arthrodesis or amputation should be explicitly discussed with patients and families when managing unstable ankle fractures in diabetic patients.

Diabetes-Related Excess Mortality in Mexico: A Comparative Analysis of National Death Registries Between 2017-2019 and 2020

OBJECTIVE

To estimate diabetes-related mortality in Mexico in 2020 compared with 2017-2019 after the onset of the coronavirus disease 2019 (COVID-19) pandemic.

RESEARCH DESIGN AND METHODS

This retrospective, state-level study used national death registries of Mexican adults aged ≥20 years for the 2017-2020 period. Diabetes-related death was defined using ICD-10 codes listing diabetes as the primary cause of death, excluding certificates with COVID-19 as the primary cause of death. Spatial and negative binomial regression models were used to characterize the geographic distribution and sociodemographic and epidemiologic correlates of diabetes-related excess mortality, estimated as increases in diabetes-related mortality in 2020 compared with average 2017-2019 rates.

RESULTS

We identified 148,437 diabetes-related deaths in 2020 (177 per 100,000 inhabitants) vs. an average of 101,496 deaths in 2017-2019 (125 per 100,000 inhabitants). In-hospital diabetes-related deaths decreased by 17.8% in 2020 versus 2017-2019, whereas out-of-hospital deaths increased by 89.4%. Most deaths were attributable to type 2 diabetes (130 per 100,000 inhabitants). Compared with 2018-2019 data, hyperglycemic hyperosmolar state and diabetic ketoacidosis were the two contributing causes with the highest increase in mortality (128% and 116% increase, respectively). Diabetes-related excess mortality clustered in southern Mexico and was highest in states with higher social lag, rates of COVID-19 hospitalization, and prevalence of HbA1c ≥7.5%.

CONCLUSIONS

Diabetes-related deaths increased among Mexican adults by 41.6% in 2020 after the onset of the COVID-19 pandemic, occurred disproportionately outside the hospital, and were largely attributable to type 2 diabetes and hyperglycemic emergencies. Disruptions in diabetes care and strained hospital capacity may have contributed to diabetes-related excess mortality in Mexico during 2020.

Applying a socioecological framework to chronic disease management: implications for social informatics interventions in safety-net healthcare settings

Objective

Vulnerable populations face numerous barriers in managing chronic disease(s). As healthcare systems work toward integrating social risk factors into electronic health records and healthcare delivery, we need better understanding of the interrelated nature of social needs within patients' everyday lives to inform effective informatics interventions to advance health equity.

Materials and Methods

We conducted in-depth interviews, participant-led neighborhood tours, and clinic visit observations involving 10 patients with diabetes in underserved San Francisco neighborhoods and 10 community leaders serving those neighborhoods. We coded health barriers and facilitators using a socioecological framework. We also linked these qualitative data with early persona development, focusing on patients' experiences in these communities and within the healthcare system, as a starting place for our future informatics design.

Results

We identified social risk and protective factors across almost every socioecological domain and level-from physical disability to household context to neighborhood environment. We then detailed the complex interplay across domains and levels within two critical aspects of patients' lives: housing and food. Finally, from these data we generated 3 personas that capture the intersectional nature of these determinants.

Conclusion

Drawing from different disciplines, our study provides a socioecological approach to understanding health promotion for patients with chronic disease in a safety-net healthcare system, using multiple methodologies. Future digital health research should center the lived experiences of marginalized patients to effectively design and implement informatics solutions for this audience.