The Association of Retinal Disease with Vision Impairment and Functional Status in Medicare Patients.

Background: The association of neovascular age-related macular degeneration (nAMD), diabetic macular edema (DME), and retinal vein occlusion (RVO) with functional status in the general Medicare population are not well established. Objectives: This study examined patient-reported survey data linked with Medicare claims to describe the burden of these vision-threatening retinal diseases (VTRDs) among Medicare beneficiaries. Methods: Medicare Current Beneficiary Survey data linked with Medicare Fee-for-Service claims data from 2006 to 2018 were used in a nationally representative retrospective pooled cross-sectional population-based comparison study. Outcomes between community-dwelling beneficiaries with nAMD (n = 1228), DME (n = 101), or RVO (n = 251) were compared with community-dwelling beneficiaries without any VTRDs (n = 104 088), controlling for baseline demographic and clinical differences. Beneficiaries with a diagnosis of nAMD, DME, or RVO during the data year were included; those with other VTRDs were excluded. Outcomes included vision function and loss, overall functioning as assessed by difficulties with activities of daily living (ADLs) and instrumental ADLs (iADLs), anxiety/depression, falls, and fractures. Results: In patient cohorts with nAMD, DME, and RVO, approximately one-third (34.2%-38.3%) reported "a little trouble seeing" (vs 28.3% for controls), and 26%, 17%, and 9%, respectively, reported "a lot of trouble seeing/blindness" (vs 5% of controls). Difficulty walking and doing heavy housework were the most reported ADLs and iADLs, respectively. Compared with those without VTRDs, beneficiaries with nAMD had higher odds of diagnosed vision loss (odds ratio [OR], 5.39; 95% confidence interval, 4.06-7.16; P < .001) and difficulties with iADLs (odds ratio, 1.41; 95% confidence interval, 1.11-1.80; P = .005); no differences were observed for DME or RVO vs control. After adjusting for age, sex, race/ethnicity, poverty status, comorbidities, and other relevant covariates, nAMD, DME, and RVO were not significantly associated with anxiety/depression, falls, or fractures. Discussion: Patients with nAMD or DME were more likely to report severe visual impairment than those without VTRDs, although only those with nAMD were more likely to be diagnosed with vision loss. Conclusions: Patients with nAMD continue to experience more vision impairment and worse functional status compared with a similar population of Medicare beneficiaries despite availability of therapies like antivascular endothelial growth factor to treat retinal disease.

Assessment of second primary malignancies among treated and untreated patients with chronic lymphocytic leukemia using real-world data from the USA.

Aim: Improved management of chronic lymphocytic leukemia (CLL) has resulted in a growing population of CLL survivors; these patients have a higher risk of developing second primary malignancies (SPMs) versus the general population. This retrospective cohort study aims to assess the timing, frequency, incidence and types of SPMs in treated and untreated patients with CLL in the USA, using the Surveillance, Epidemiology, and End Results (SEER) Medicare database, which links a nationally representative cancer registry with Medicare claims data. Patients & methods: Patients aged ≥66 years with newly diagnosed CLL between 1 January 2010 and 31 December 2016, who were enrolled in Parts A and B of Medicare for ≥12 months pre-diagnosis of CLL were selected from the database. Patients were assessed for ≥36 months until the end of continuous enrollment in Medicare Parts A, B and D, a switch to a health maintenance organization, death, or end of the study period (December 2019). Results: Of 3053 patients included in the analyses, 620 (20.3%) were treated and 2433 (79.7%) were untreated within 36 months of diagnosis. Overall, 638 (20.9%) patients developed a SPM, 26.8% of patients in the treated cohort and 19.4% of patients in the untreated cohort. The most common SPMs for both cohorts were squamous cell carcinoma and acute myeloid leukemia. Among the 166 treated patients who developed a SPM, a greater proportion developed their first SPM after treatment initiation versus those who developed their first SPM prior to treatment initiation (p < 0.001). A significantly lower percentage of patients who received targeted therapy developed a SPM (p < 0.05) versus patients treated with anti-CD20 + chemotherapy. Conclusion: Findings indicate that treatment type and timing can affect SPM development in patients with CLL. Combined with previous findings, this can help inform best practices in monitoring for SPM in patients with CLL.

Clinical Outcomes in Patients With Refractory Anemia With Excess Blasts (RAEB) Who Receive Hypomethylating Agents (HMAs).

BACKGROUND: We sought to understand the clinical effectiveness associated with use of hypomethylating agents (HMAs) azacitidine (AZA) and decitabine (DEC) for patients with refractory anemia with excess blasts (RAEB; an established proxy for higher-risk myelodysplastic syndromes/neoplasms) in contemporary and representative real-world settings. PATIENTS AND METHODS: We used the Surveillance, Epidemiology and End Results (SEER)-Medicare database, a linkage of cancer registry and Medicare claims data, to identify patients aged ≥ 66 years diagnosed with RAEB, between 2009 and 2017 in the United States, and who received AZA or DEC as first-line therapy. Outcomes measured were overall survival (OS), event-free survival (EFS), and incidence of progression-related acute myeloid leukemia (AML). RESULTS: Of 973 eligible patients, 738 (75.8%) received AZA and 235 (24.2%) received DEC; 6.4% received hematopoietic cell transplantation during follow-up. In the overall population, median OS was 13.9 months (95% confidence interval [CI]: 12.9-15.0), median EFS was 5.2 months (95% CI: 4.9-5.7), and 38.0% of patients progressed to AML. Incidences of AML progression and death were 25.6% and 29.9%, respectively, at Year 1, and 34.3% and 44.8%, respectively, at Year 2. There were no significant differences in clinical benefits between AZA and DEC. CONCLUSION: Median OS with both HMAs remained significantly shorter than in the AZA-001 clinical trial, highlighting how patient outcomes vary between clinical and real-world settings. Further research is required to understand why these disparities exist.

US cost-effectiveness analysis of polatuzumab vedotin in previously untreated diffuse large B-cell lymphoma.

AIMS: We evaluated the pharmacoeconomic value of polatuzumab vedotin plus rituximab, cyclophosphamide, doxorubicin, and prednisone (Pola-R-CHP) in previously untreated diffuse large B-cell lymphoma (DLBCL) versus rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). MATERIALS AND METHODS: A 3-state partitioned survival model was used to estimate life years (LYs), quality-adjusted LYs (QALYs), and cost impacts of Pola-R-CHP versus R-CHOP. Analyses utilized mixture-cure survival modelling, assessed a lifetime horizon, discounted all outcomes at 3% per year, and examined both payer and societal perspectives. Progression-free survival, overall survival (OS), drug utilization, treatment duration, adverse reactions, and subsequent treatment inputs were based on data from the POLARIX study (NCT03274492). Costs included drug acquisition/administration, adverse reaction management, routine care, subsequent treatments, end-of-life care, and work productivity. RESULTS: Incremental cost-effectiveness ratios of Pola-R-CHP versus R-CHOP were $70,719/QALY gained and $88,855/QALY gained from societal and payer perspectives, respectively. The $32,824 higher total cost of Pola-R-CHP versus R-CHOP was largely due to higher drug costs ($122,525 vs $27,694), with cost offsets including subsequent treatment (-$52,765), routine care (-$1,781), end-of-life care (-$383), and work productivity (-$8,418). Pola-R-CHP resulted in an increase of 0.47 LYs and 0.46 QALYs versus R-CHOP. Pola-R-CHP was cost-effective in 60.9% and 58.0% of simulations at a willingness-to-pay threshold of $150,000/QALY gained from societal and payer perspectives, respectively. LIMITATIONS: There was uncertainty around the OS extrapolation in the model, and costs were derived from different sources. Recommended prophylactic medications were not included; prophylactic use of granulocyte colony-stimulating factor for all patients was assumed to be equal across treatment arms in POLARIX. Work productivity loss was estimated from a general population and was not specific to patients with DLBCL. CONCLUSION: Pola-R-CHP was projected to be cost-effective versus R-CHOP in previously untreated DLBCL, suggesting that Pola-R-CHP represents good value relative to R-CHOP in this setting.

Cost of Disease Progression in Diffuse Large B-Cell Lymphoma After Frontline Treatment With Rituximab Plus Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone.

BACKGROUND: In recent years, novel agents have become available to treat relapsed/refractory diffuse large B-cell lymphoma (DLBCL); the impact of such agents on treatment costs has not been formally studied. We present results from 2 independent, retrospective, real-world cohort analyses to determine the cost of disease progression after first-line rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). MATERIALS AND METHODS: Analyses were conducted using the IQVIA PharMetricsⓇ Plus claims database and the Surveillance, Epidemiology, and End Results registry-Medicare-linked database (SEER-Medicare) and included patients ≥18 years and ≥66 years, respectively. "No progression" was defined as no second-line therapy for ≥2 years after the end of first-line R-CHOP and "treated progression" as initiating a second-line therapy within 2 years following the end of first-line R-CHOP. Analyses were adjusted for baseline covariates, and per-patient-per-month (PPPM) costs were compared between progressors and nonprogressors. RESULTS: The IQVIA PharMetrics Plus analysis (January 1, 2010-June 30, 2018) included 871 patients (nonprogressors, n = 725; progressors, n = 146), including 10 patients who received chimeric antigen receptor T-cell therapy (CAR-T). Treated progression was associated with significantly higher adjusted PPPM costs than no progression ($10,554 vs. $1561, P < .001). The SEER-Medicare analysis (January 1, 2010-December 31, 2017) included 4099 patients (nonprogressors, n = 3389; progressors, n = 710), including 12 patients receiving CAR-T. Treated progression was associated with significantly higher adjusted PPPM costs than no progression ($10,928 vs. $2902, P < .001). CONCLUSION: Treated progression of DLBCL increases adjusted PPPM costs by over $8000 compared with no progression.

Estimating the US Baseline Distribution of Health Inequalities Across Race, Ethnicity, and Geography for Equity-Informative Cost-Effectiveness Analysis.

OBJECTIVES: Information on how life expectancy, disability-free life expectancy, and quality-adjusted life expectancy varies across equity-relevant subgroups is required to conduct distributional cost-effectiveness analysis. These summary measures are not comprehensively available in the United States, given limitations in nationally representative data across racial and ethnic groups. METHODS: Through linkage of US national survey data sets and use of Bayesian models to address missing and suppressed mortality data, we estimate health outcomes across 5 racial and ethnic subgroups (non-Hispanic American Indian or Alaska Native, non-Hispanic Asian and Pacific Islander, non-Hispanic black, non-Hispanic white, and Hispanic). Mortality, disability, and social determinant of health data were combined to estimate sex- and age-based outcomes for equity-relevant subgroups based on race and ethnicity, as well as county-level social vulnerability. RESULTS: Life expectancy, disability-free life expectancy, and quality-adjusted life expectancy at birth declined from 79.5, 69.4, and 64.3 years, respectively, among the 20% least socially vulnerable (best-off) counties to 76.8, 63.6, and 61.1 years, respectively, among the 20% most socially vulnerable (worst-off) counties. Considering differences across racial and ethnic subgroups, as well as geography, gaps between the best-off (Asian and Pacific Islander; 20% least socially vulnerable counties) and worst-off (American Indian/Alaska Native; 20% most socially vulnerable counties) subgroups were large (17.6 life-years, 20.9 disability-free life-years, and 18.0 quality-adjusted life-years) and increased with age. CONCLUSIONS: Existing disparities in health across geographies and racial and ethnic subgroups may lead to distributional differences in the impact of health interventions. Data from this study support routine estimation of equity effects in healthcare decision making, including distributional cost-effectiveness analysis.

The Impact of Funding Inpatient Treatments for COVID-19 on Health Equity in the United States: A Distributional Cost-Effectiveness Analysis.

OBJECTIVES: We conducted a distributional cost-effectiveness analysis (DCEA) to evaluate how Medicare funding of inpatient COVID-19 treatments affected health equity in the United States. METHODS: A DCEA, based on an existing cost-effectiveness analysis model, was conducted from the perspective of a single US payer, Medicare. The US population was divided based on race and ethnicity (Hispanic, non-Hispanic black, and non-Hispanic white) and county-level social vulnerability index (5 quintile groups) into 15 equity-relevant subgroups. The baseline distribution of quality-adjusted life expectancy was estimated across the equity subgroups. Opportunity costs were estimated by converting total spend on COVID-19 inpatient treatments into health losses, expressed as quality-adjusted life-years (QALYs), using base-case assumptions of an opportunity cost threshold of $150 000 per QALY gained and an equal distribution of opportunity costs across equity-relevant subgroups. RESULTS: More socially vulnerable populations received larger per capita health benefits due to higher COVID-19 incidence and baseline in-hospital mortality. The total direct medical cost of inpatient COVID-19 interventions in the United States in 2020 was estimated at $25.83 billion with an estimated net benefit of 735 569 QALYs after adjusting for opportunity costs. Funding inpatient COVID-19 treatment reduced the population-level burden of health inequality by 0.234%. Conclusions remained robust across scenario and sensitivity analyses. CONCLUSIONS: To the best of our knowledge, this is the first DCEA to quantify the equity implications of funding COVID-19 treatments in the United States. Medicare funding of COVID-19 treatments in the United States could improve overall health while reducing existing health inequalities.

The Association Between Persistence and Adherence to Disease-Modifying Therapies and Healthcare Resource Utilization and Costs in Patients With Multiple Sclerosis.

Background: Persistence and adherence to disease-modifying therapies (DMTs) affects treatment efficacy and economic outcomes, both of which contribute to overall patient disease burden. Current literature suggests that patients with multiple sclerosis (MS) who adhere to DMT for 12 months have fewer relapses and reduced MS-related healthcare resource utilization (HCRU) and medical costs than nonadherent patients. Objective: To expand on previous research by estimating the association of persistence and adherence with all-cause and MS-related HCRU and non-DMT costs of patients with MS across 12 and 24 months of therapy use. Methods: This study was a retrospective analysis of adult patients with MS in the IBM MarketScan Commercial and Medicare Supplemental databases using claims data between April 2016 and December 2019. The index date was defined as the initiation of the DMT. Patients were required to have ≥12 months' continuous enrollment pre-index and ≥12 or ≥24 months' continuous enrollment post-index. Persistence was defined as no gap in DMT supply for ≥60 days within the post-index period or switch to another DMT. Adherence was calculated using the proportion of days covered (for this study, number of days covered by the DMT was 365 or 730 days), with ≥80% proportion of days covered considered adherent. Multivariable analyses were conducted to estimate total and individual components of non-DMT costs by persistence and adherence while controlling for baseline differences. Results: Patients who were persistent with medication for 12 months showed a reduction in mean total non-DMT medical costs of $10 022 compared with nonpersistent patients; these savings nearly doubled ($19 230) after 24 months of persistence. A similar pattern was observed for adherent vs nonadherent patients (reduction in costs at 12 months, $8543; at 24 months, $16 091). The largest reduction in all-cause HCRU costs was observed in the inpatient setting, while the largest reduction in MS-related costs was observed in the outpatient setting. Discussion: Patients with MS who were persistent and adherent to medication had substantially lower all-cause and MS-related non-DMT medical costs compared with those who were nonpersistent or nonadherent. Conclusions: These findings further support the importance of persistence and adherence to DMTs in patients with MS.

Adherence to and Persistence with Disease-Modifying Therapies for Multiple Sclerosis Over 24 Months: A Retrospective Claims Analysis.

INTRODUCTION: We sought to assess adherence to and persistence with ocrelizumab (OCR) compared with other disease-modifying treatments (DMTs), by route of administration (RoA), for multiple sclerosis (MS) after 24 months in the United States. METHODS: This retrospective claims analysis of MS patients initiating a new DMT was conducted using the IBM MarketScan Commercial and Medicare Supplemental databases between April 2016 and December 2019. Continuous enrollment of ≥ 12 months before and up to 24 months after initiating the index DMT was required. Adherence was assessed based on proportion of days covered (PDC) in the follow-up period with values ≥ 80% considered adherent. Persistence was defined as no evidence of switching to another DMT or no gap ≥ 60 days in DMT coverage. RESULTS: A total of 1710 patients with ≥ 24 months of follow-up (OCR, n = 524; oral, n = 701; injectable, n = 365; other intravenous [IV], n = 120) were included. Patients initiating OCR had higher adherence (80% vs. 55%, 35%, and 54% for oral, injectable, and other IV, respectively) and persistence (75% vs. 54%, 33%, and 55%, respectively) at 24 months. Relative risks (RRs) of 24-month non-adherence for those initiating orals, injectables, and other IVs were 2.2 (95% CI, 1.7-2.9), 3.0 (95% CI, 2.2-4.0), and 2.2 (95% CI, 1.5-3.3), respectively, compared to those initiating OCR. Similarly, patients receiving orals, injectables, and other IVs had RR of 1.9 (95% CI, 1.4-2.4), 2.5 (95% CI, 1.9-3.4), and 1.8 (95% CI, 1.2-2.6) for 24-month discontinuation, respectively. Similar patterns were observed at 12 and 18 months. CONCLUSIONS: Patients initiating OCR in a real-world setting achieved higher rates of adherence and persistence at 24 months compared with those initiating other DMTs, consistent with published literature showing similar results at 12 and 18 months. Optimizing medication adherence and persistence is fundamental to MS care, so clinicians should consider all elements of DMTs that may improve compliance.

Persistence and adherence to ocrelizumab compared with other disease-modifying therapies for multiple sclerosis in U.S. commercial claims data.

BACKGROUND: Ocrelizumab (OCR) is the only disease-modifying therapy (DMT) for both relapsing and primary progressive forms of multiple sclerosis (MS). OCR is given by intravenous (IV) infusion twice a year, which may improve adherence to the dosing schedule relative to other MS DMTs that require more frequent administration. Real-world evidence on the persistence and adherence of patients with MS to OCR compared with other DMTs is limited. OBJECTIVE: To examine the persistence and adherence to OCR compared with other DMTs for MS in the United States. METHODS: This analysis was conducted in the PharMetrics Plus commercial claims database and included patients with MS who initiated a new DMT between April 2017 and September 2018. Patients were required to have health plan enrollment for ≥ 1 year before and after DMT initiation (a subgroup analysis was performed for those with ≥ 18 months' continuous enrollment after DMT initiation). Persistence was defined as not switching to another DMT and having no gap in coverage of the initiated DMT for ≥ 60 days during the postinitiation period. The proportion of days covered (PDC) was calculated as the total days covered by the DMT during the postinitiation period divided by the length of the time period (12 or 18 months); PDC ≥ 0.8 was considered adherent. Multivariable Poisson regression models compared discontinuation (nonpersistence) and nonadherence between OCR users and users of other DMTs grouped by administration route. RESULTS: A total of 4,587 patients (OCR, 1,319; injectable, 1,051; oral, 1,876; other IV, 341) were included. The OCR group had the lowest proportion of patients discontinuing at 12 months (8% vs. 28%, 32%, and 43% for other IV, oral, and injectable, respectively) and the highest mean PDC (93% vs. 76%, 74%, and 69%, respectively). Compared with patients initiating OCR, adjusted relative risks (RR) of 12-month discontinuation were 3.3 (95% CI = 2.3-4.6), 3.8 (95% CI = 3.0-4.9), and 5.5 (95% CI = 4.1-7.5) for patients initiating other IV, oral, and injectable DMTs, respectively. Similarly, patients initiating other IV, oral, and injectable DMTs had RRs of 4.9 (95% CI = 3.6-6.8), 5.1 (95% CI = 3.9-6.6), and 6.8 (95% CI = 5.0-9.3) for 12-month nonadherence compared with OCR. A subgroup of 2,913 patients with 18 months of continuous enrollment had similar trends, with 17% in the OCR group discontinuing compared with 40%, 41%, and 55% in the other IV, oral, and injectable groups, respectively. Trends over 18 months were consistent with the 12-month analysis in adjusted models. CONCLUSIONS: Patients initiating OCR had superior persistence and adherence at 12 and 18 months of follow-up compared with patients initiating other MS DMTs. Long-term persistence and adherence should be monitored as OCR experience accrues in a real-world setting. DISCLOSURES: This study was funded by Genentech (South San Francisco, CA), a member of the Roche Group. Engmann, Sheinson, Bawa, and Ng are employees of Genentech and shareholders of F. Hoffman-La Roche (Basel, Switzerland).

Beyond recent BMI: BMI exposure metrics and their relationship to health.

Body mass index (BMI) is generally used to classify adiposity. Despite the fact that the consequences of adiposity for chronic health accumulate and manifest over time, most population health research exploring the implications of high BMI measures only its recent intensity. Some studies have used retrospective measures involving maximum weight, and even fewer have used BMI at multiple time points to estimate cumulative exposure to adiposity. The goal of this study was to compare BMI exposure metrics that captured different dimensions of body mass - intensity, history, and duration - in models of health indicators linked with adiposity. We used self-reported BMI of young adults (ages 18 - 33 years, n = 8,608) across 11 waves of data from the National Longitudinal Survey of Youth 1997 to evaluate eight BMI exposure metrics: most recent, maximum, mean, and median BMI, proportion of time with overweight/obesity, and excess BMI-years with overweight/obesity. We used these metrics in models of self-reported general health, chronic condition, and diabetes, and ascertained how most recent BMI performed when compared with other metrics that better capture the dynamics of BMI. The Akaike information criteria and Vuong tests were used for model comparison, and the strengths of associations were also compared. Most recent BMI was the best metric for explaining general health. Median BMI was best for explaining diabetes, with most recent BMI under-estimating the association by 13% relative to median BMI. For chronic condition, there was no clear best metric. We concluded that most recent BMI is useful for explaining health outcomes, though other metrics should also be given consideration, particularly for conditions that develop over time. Metrics that accounted for both intensity and history performed quite well, but the duration measures might be less useful.

In, out, and fluctuating: obesity from adolescence to adulthood.

PURPOSE: While high levels of obesity prevalence and incidence have been well documented, there is less research on obesity dynamics over time. In this article, we sought to understand the body mass index (BMI) trajectories in and out of obesity from adolescence to adulthood. METHODS: We used the National Longitudinal Study of Adolescent to Adult Health to explore American obesity dynamics from mean ages 15-28 years. We analyzed six BMI trajectories from 1994 to 2008 and examined their contextual sociodemographic correlates using ordinal logistic regression models. RESULTS: More than 50% of adolescents with normal BMI moved to overweight/obesity by adulthood; only 8% of overweight and 2% of obese adolescents achieved normal BMI in adulthood. While some sociodemographic characteristics such as sex, race/ethnicity, place of residence, and parents' education were associated with being in certain BMI trajectories among adolescents with normal BMI, they were not so associated among adolescents starting at obesity. CONCLUSIONS: Transitioning to higher BMI categories was common, whereas the opposite direction was rare. Pathways to obesity prevention might be easier to identify than those to reversal, as contextual factors had more explanatory power for youths with normal BMI than for those with obese BMI.

What your genes can (and can't) tell you about BMI and diabetes.

Body mass index (BMI) is commonly used as a proxy for adiposity in epidemiological and public health studies. However, BMI may suffer from issues of misreporting and, because it fluctuates over the life course, its association with morbidities such as diabetes is difficult to measure. We examined the associations between actual BMI, genetic propensity for high BMI, and diabetes to better understand whether a BMI polygenic score (PGS) explained more variation in diabetes than self-reported BMI. We used a sample of non-Hispanic white adults from the longitudinal Health and Retirement Study (1992-2016). Structural equation models were used to determine how much variation in BMI could be explained by a BMI PGS. Then, we used logistic regression models (n = 12,086) to study prevalent diabetes at baseline and Cox regression models (n = 11,129) to examine incident diabetes with up to 24 years of follow-up. We observed that while both actual BMI and the BMI PGS were significantly associated with diabetes, actual BMI had a stronger association than its genetic counterpart and resulted in better model performance. Moreover, actual BMI explained more variation in baseline and incident diabetes than its genetic counterpart which may suggest that actual BMI captures more than just adiposity as intended.

Stratification of BMI categories among older adults within and across countries.

OBJECTIVE: Within- and across-country nutritional disparities were examined among older adults in six different countries at varying levels of development. DESIGN: Cross-sectional study. PARTICIPANTS: Older adults (aged 50 years or over) in China, Ghana, India, Mexico, Russia and South Africa using the Study on global AGEing and adult health (SAGE). RESULTS: While the distribution of BMI categories varied by country, development-related characteristics were generally related to BMI category in a similar way: urban-living, educated and wealthier individuals were typically more likely to be in a higher BMI category. However, there were some exceptions that corroborate findings in more developed countries. Indeed, a pooled partial proportional odds model which included gross domestic product per capita interactions made the case for intertwining processes of development and the nutrition transition. CONCLUSIONS: Population segments to be targeted by nutrition policy and programme implementation might need to change over the course of development.

Association of genetic and behavioral characteristics with the onset of diabetes.

BACKGROUND: Prior work has established sociodemographic, lifestyle, and behavioral risk factors for diabetes but the contribution of these factors to the onset of diabetes remains unclear when accounting for genetic propensity for diabetes. We examined the contribution of a diabetes polygenic score (PGS) to the onset of diabetes in the context of modifiable known risk factors for diabetes. METHODS: Our sample consisted of 15,190 respondents in the United States-based Health and Retirement Study, a longitudinal study with up to 22 years of follow-up. We performed multivariate Cox regression models stratified by race (non-Hispanic white and non-Hispanic black) with time-varying covariates. RESULTS: We observed 4217 (27.76%) cases of incident diabetes over the survey period. The diabetes PGS was statistically significantly associated with diabetes onset for both non-Hispanic whites (hazard ratio [HR] = 1.38, 95% confidence interval [CI] = 1.30, 1.46) and non-Hispanic blacks (HR = 1.22, 95% CI = 1.06, 1.40) after adjusting for a range of known risk factors for diabetes, highlighting the critical role genetic endowment might play. Nevertheless, genetics do not downplay the role that modifiable characteristics could still play in diabetes management; even with the inclusion of the diabetes PGS, several behavioral and lifestyle characteristics remained significant for both race groups. CONCLUSIONS: The effects of genetic and lifestyle characteristics should be taken into consideration for both future studies and diabetes management.

Errors in body mass index from self-reported data by sex and across waves of Add Health.

PURPOSE: Body mass index (BMI) derived from self-reported height and weight is often used to study adiposity and its health implications. However, misestimates of BMI from self-reported data have been observed. This study adds to the literature by demonstrating how anthropometric misreporting patterns differed by sex and changed across time in a nationally representative cohort, as well as examining behavioral/psychological correlates of biases in BMI. METHODS: Misreporting of height and weight (and thus BMI) from adolescence to adulthood in the United States was studied using the National Longitudinal Study of Adolescent to Adult Health (1996-2008). Behavioral/psychological characteristics possibly associated with errors in BMI were analyzed with fixed-effects models. RESULTS: Different patterns of anthropometric misreporting resulted in larger underestimation of BMI among females than males at the beginning waves, but females saw a reduction by the last wave. Males did not see such a decrease, and their error, at 0.75 BMI units by 2008, was comparable to that of females. For both sexes, body image perception was a significant predictor of biases in BMI. CONCLUSIONS: From adolescence to adulthood, anthropometric reporting patterns changed, and its variation differed by sex. Nevertheless, errors in BMI were similarly associated with behavioral/psychological characteristics.

Biases in self-reported height and weight measurements and their effects on modeling health outcomes.

Self-reported anthropometrics are often used as proxies for measured anthropometrics, but research has shown that heights and weights are often misreported. Using the Study on global AGEing and adult health, I analyze misreporting patterns of height, weight, and BMI in China, India, Russia, and South Africa. Adjustments of self-reported heights and weights using demographic, social, and anthropometric characteristics are evaluated and found to be useful in studying the distribution of anthropometrics within a population. Measured, self-reported, and adjusted BMI are then compared in logistic regression models on the reporting of health outcomes, as well as the resulting accuracy of individual prediction. When BMI is used as a continuous variable in models of health outcomes, measured, self-reported, and adjusted BMI produce similar coefficient estimates, and so self-reported data would be a natural choice because of its accessibility and convenience. In other applications, such as models using categorical BMI and individual prediction using either continuous or categorical BMI, self-reported data in lieu of measured data might not be accurate enough, but adjustments could serve as a potential compromise.

FROM BIRTH TO ADULTHOOD: ANTHROPOMETRIC TRAJECTORIES AND THEIR IMPLICATIONS FOR CHRONIC DISEASES IN GUATEMALA.

The objective of this paper was to study nutritional status and growth, as measured by height and weight, over the life course and their connection with chronic diseases in Guatemala, a country with high levels of child undernutrition and adult overnutrition, using data from the Institute of Nutrition of Central America and Panama (INCAP) Nutrition Trial Cohort study. The study sample comprised a birth cohort of 1570 individuals who had data in the original 1969-1977 survey as well as the 2002-2004 follow-up, allowing for an analysis of the nutritional transition from childhood to adulthood. The associations between childhood and adulthood anthropometrics were analysed, and the links of these with chronic disease indicators were assessed using multiple regression analysis and structural equation modelling. Moving upwards in nutritional status from childhood to adulthood was observed frequently in the study population. Unlike sex and place of residence, early anthropometrics were not generally found to be associated with adult body mass index (BMI). However, direct relationships were found between childhood nutritional status and growth and adulthood high-density lipoprotein (HDL) cholesterol, triglycerides and fasting blood glucose. Furthermore, these relationships were not mediated by BMI. The findings were not sensitive to the metric of childhood anthropometrics, as the use of length-for-age, weight-for-age and weight-for-length all resulted in similar conclusions. These relationships demonstrate the importance of early childhood conditions for later-life outcomes. However, the lack of such relationships for blood pressure suggests that the biological links between childhood anthropometrics and various chronic diseases might vary.

Global analysis of overweight prevalence by level of human development.

BACKGROUND: Less developed countries are increasingly afflicted with over-nutrition, and the escalating overweight prevalence has become a global problem. However, a problem as global as this may not be amenable to a general set of remedial interventions applicable to all countries. METHODS: I use data from various sources, including the World Health Organization and the World Bank, to test the association of overweight prevalence with economic, social, and demographic indicators. I then split the countries up by human development index to investigate to what extent these associations vary between development levels. FINDINGS: On a global scale, overweight prevalence is most associated with gross domestic product (GDP) per capita, the proportion of a country that is rural, the proportion of elderly in a country's population, and the average years of schooling. At what magnitude, and even in which direction, these relationships go vary with a country's level of development. Generally, GDP per capita has a positive association with overweight prevalence, with the magnitude of such association for countries of very high human development more than twice of that for countries of low human development. However, proportion rural has a negative association with overweight prevalence, with the magnitude of such association for countries of low human development nearly twice of that for countries of very high human development. All four of these variables have statistically significant association with overweight prevalence in countries with low human development. CONCLUSIONS: I make policy suggestions to combat increasing overweight prevalence, based on the models that are developed, paying special attention to the differences in magnitude and direction of the regressors between human development levels.