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Modeled state-level estimates of hypertension prevalence and undiagnosed hypertension among US adults during 2013-2015.

ABSTRACT: Hypertension affects about one in three US adults, from recent surveillance, or four in nine based on the 2017 ACC/AHA Hypertension Guideline; about half of them have their blood pressure controlled, and nearly one in six are unaware of their hypertension status. National estimates of hypertension awareness, treatment, and control in the United States are traditionally based on measured BP from National Health and Nutrition Examination Survey (NHANES); however, at the state level, only self-reported hypertension awareness and treatment are available from BRFSS. We used national- and state-level representative samples of adults (≥20 years) from NHANES 2011-2014 and BRFSS 2013 and 2015, respectively. The authors generated multivariable logistic regression models using NHANES to predict the probability of hypertension and undiagnosed hypertension and then applied the fitted model parameters to BRFSS to generate state-level estimates. The predicted prevalence of hypertension was highest in Mississippi among adults (42.4%; 95% CI: 41.8-43.0) and among women (42.6%; 41.8-43.4) and highest in West Virginia among men (43.4%; 42.2-44.6). The predicted prevalence was lowest in Utah 23.7% (22.8-24.6), 26.4% (25.0-27.7), and 21.0% (20.0-22.1) for adults, men, and women, respectively. Hypertension predicted prevalence was higher in most Southern states and higher among men than women in all states except Mississippi and DC. The predicted prevalence of undiagnosed hypertension ranged from 4.1% (3.4-4.8; Kentucky) to 6.5% (5.5-7.5; Hawaii) among adults, from 5.0% (4.0-5.9; Kentucky) to 8.3% (6.9-9.7; Hawaii) among men, and from 3.3% (2.5-4.1; Kentucky) to 4.8% (3.4-6.1; Vermont) among women. Undiagnosed hypertension was more prevalent among men than women in all states and DC.

SUBMITTER: Park S

PROVIDER: S-EPMC8031025 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionImproving hypertension control is a national priority. Electronic health record data have the potential to augment traditional surveillance systems. This study aimed to assess hypertension prevalence and control at the state level using a previously established electronic health record-based phenotype for hypertension.MethodsAdult patients (N=11,031,368) were included from the IQVIA ambulatory electronic medical record-U.S. 2019 data set. IQVIA ambulatory electronic medical record comprises electronic health records from >100,000 providers and includes patients from every U.S. state and Washington DC. Authors compared hypertension prevalence and control estimates against those from the Behavioral Risk Factor Surveillance System 2019. Results were age-standardized and stratified by state and sociodemographic characteristics. Statistical analyses were conducted in 2022-2023.ResultsIQVIA ambulatory electronic medical record-U.S. patients had a median age of 55 years, and 56.7% were women. Overall age-standardized hypertension prevalence was higher in IQVIA ambulatory electronic medical record-U.S. (35.0%) than in the Behavioral Risk Factor Surveillance System (29.7%), however, state-level geographic patterns were similar, with the highest burden in the South and Appalachia. Similar patterns were also observed by sociodemographic characteristics in both data sets: hypertension prevalence was higher in older age groups (than younger), men (than women), and Black patients (than other races). Hypertension control varied widely across states: among states with >1% data coverage, control rates were lowest in Nevada (51.1%), Washington DC (52.0%), and Mississippi (55.2%); highest in Kansas (73.4%), New Jersey (72.3%), and Iowa (71.9%).ConclusionsThis study provided the first-ever estimates of hypertension control for all states and Washington DC. Electronic health record-based surveillance could support hypertension prevention and control efforts at the state level.

Project description:BackgroundAtrial fibrillation (AF) prevalence estimates vary and have been based on cohorts with clinically established or diagnosed disease. Undiagnosed AF prevalence estimates are less certain as they are based on nongeneralizable convenience samples.HypothesisBecause AF is often asymptomatic, it my remain undiagnosed until the development of complications such as stroke or heart failure. Consequently, the observed prevalence of diagnosed AF from the literature may underestimate total disease burden. We therefore sought to estimate the total prevalence of both diagnosed and undiagnosed AF.MethodsWe performed a retrospective cohort study from 2012 to 2017 using data from five US medical claims data sets. Undiagnosed AF prevalence was estimated based on the observed incidence of ischemic stroke, systemic embolism (SE), and AF incidence after a stroke/SE. The diagnosed AF cohort included AF patients between Q1 2014 and Q3 2015. The undiagnosed AF cohort were patients with assumed undiagnosed AF in the year before a stroke/SE and who were newly diagnosed with AF in the 3-month poststroke/SE. Stroke/SE incidence was calculated among all AF patients and the ratio of number of undiagnosed AF patients to stroke rate was created. Age- and sex-adjusted estimates were stratified by period of assumed undiagnosed AF before poststroke/SE AF diagnosis (1 or 2 years).ResultsThe estimated US prevalence of AF (diagnosed and undiagnosed) in Q3 2015 was 5 628 000 cases, of which 591 000 cases (11%) were undiagnosed. The assumed 2-year undiagnosed AF prevalence was 23% (1 531 000) of the total prevalent patients with AF (6 568 000). Undiagnosed (vs. diagnosed) AF patients were older and had higher CHA2DS2-VASc scores. Of undiagnosed AF, 93% had CHA2DS2-VASc ≥2 and met OAC criteria.ConclusionsThese contemporary estimates demonstrate the high prevalence of undiagnosed AF in the United States. Undiagnosed AF patients are composed of primarily elderly individuals who if diagnosed, would meet criteria for stroke prevention therapy.

Project description:BackgroundNon-communicable diseases, including hypertension (HTN), are increasingly recognized as important causes of morbidity and mortality among people living with HIV (PLHIV) in resource-limited settings. The goals of this study were to determine the prevalence of HTN among PLHIV in Senegal over time and to identify predictors of HTN among HIV-positive versus HIV-negative adults.MethodsWe conducted a retrospective study using data from individuals enrolled in previous studies in Senegal from 1994-2015. Blood pressure (BP) measurements taken during study visits were used for analysis. HTN was defined as systolic BP?140 or diastolic BP?90. We used logistic regression to identify predictors of HTN.ResultsWe analyzed data from 2848 adults (1687 HIV-positive, 1161 HIV-negative). Among PLHIV, the prevalence of HTN increased from 11% during 1994-1999 to 22% during 2010-2015. Among HIV-negative individuals, the prevalence of HTN increased from 16% to 32%. Among both groups, the odds of HTN more than doubled from 1994-1999 to 2010-2015 (HIV-positive OR 2·4, 95% CI 1·1-5·0; HIV-negative OR 2·6, 95% CI 1·5-4·6). One quarter of all individuals with HTN had stage 2 HTN. The strongest risk factor for HTN was obesity (HIV-positive OR 3·2, 95% CI 1·7-5·8; p<0·01; HIV-negative OR 7·8, 95% CI 4·5-13·6; p<0·01). Male sex and age ?50 were also predictive of HTN among both groups. Among HIV-positive subjects, WHO stage 1 or 2 disease was predictive of HTN and among HIV-negative subjects, having no formal education was predictive.ConclusionOver the past 20 years, the prevalence of HTN has doubled among both HIV-positive and HIV-negative adults in Senegal. Our study indicates that there is an increasing need for the integration of chronic disease management into HIV programs in Senegal. Furthermore, our findings highlight the need for enhanced prevention, recognition, and management of non-communicable diseases, including hypertension and obesity, among both HIV-positive and HIV-negative individuals in Senegal.

Project description:BackgroundThe absolute number of pneumonia deaths in India has declined substantially since 2000. However, pneumonia remains a major cause of morbidity in children in the country. We used a risk factor-based model to estimate pneumonia and severe pneumonia morbidity in Indian states in 2000 and 2015.MethodsIn this modelling study, we estimated the burden of pneumonia and severe pneumonia in children younger than 5 years using a risk factor-based model. We did a systematic literature review to identify published data on the incidence of pneumonia from community-based longitudinal studies and calculated summary estimates. We estimated state-specific incidence rates for WHO-defined clinical pneumonia between 2000 and 2015 using Poisson regression and the prevalence of risk factors in each state was obtained from National Family Health Surveys. From clinical pneumonia studies, we identified studies reporting the proportion of clinical pneumonia cases with lower chest wall indrawing to estimate WHO-defined severe pneumonia cases. We used the estimate of the proportion of cases with lower chest wall indrawing to estimate WHO-defined severe pneumonia cases for each state.FindingsBetween 2000 and 2015, the estimated number of pneumonia cases in Indian HIV-uninfected children younger than 5 years decreased from 83·8 million cases (95% uncertainty interval [UI] 14·0-300·8) to 49·8 million cases (9·1-174·2), representing a 41% reduction in pneumonia cases. The incidence of pneumonia in children younger than 5 years in India was 657 cases per 1000 children (95% UI 110-2357) in 2000 and 403 cases per 1000 children (74-1408) in 2015. The estimated national pneumonia case fatality rate in 2015 was 0·38% (95% UI 0·11-2·10). In 2015, the estimated number of severe pneumonia cases was 8·4 million (95% UI 1·2-31·7), with an incidence of 68 cases per 1000 children (9-257) and a case fatality ratio of 2·26% (0·60-16·30). In 2015, the estimated number of pneumonia cases in HIV-uninfected children was highest in Uttar Pradesh (12·4 million [95% UI 2·1-45·0]), Bihar (7·3 million [1·3-26·1]), and Madhya Pradesh (4·6 million [0·7-17·0]). Between 2000 and 2015, the greatest reduction in pneumonia cases was observed in Kerala (82% reduction). In 2015, pneumonia incidence was greater than 500 cases per 1000 children in two states: Uttar Pradesh (565 cases per 1000 children [95% UI 94-2047]) and Madhya Pradesh (563 cases per 1000 children [88-2084]).InterpretationThe estimated number of pneumonia and severe pneumonia cases among children younger than 5 years in India decreased between 2000 and 2015. Improvements in socioeconomic indicators and specific government initiatives are likely to have contributed to declines in the prevalence of pneumonia risk factors in many states. However, pneumonia incidence in many states remains high. The introduction of new vaccines that target pneumonia pathogens and reduce risk factors will help further reduce the burden of pneumonia in the country.FundingBill & Melinda Gates Foundation.

Project description:BackgroundHypertension is responsible for many premature deaths worldwide. However, many individuals with hypertension remain undiagnosed. Tonga is one of the countries that has had a steep increase in hypertension, thus undiagnosed hypertension could also be increasing. Purpose of this study was to assess the prevalence and factors associated with undiagnosed hypertension among Tongan adults.MethodsThis cross-sectional study used data collected from conveniently sampled 473 participants using electronic questionnaire and digital sphygmomanometer through household visits between February and March 2023. Inclusion criteria were age of 18-65 years, residence in the villages for at least six months, and not being pregnant. Fisher's exact test and mixed-effect logistic regression were performed using the EZR software to assess the association between undiagnosed hypertension and predictor variables.ResultsThe prevalence of undiagnosed hypertension was 22.4% (106/473). Five variables that were significantly associated with undiagnosed hypertension in Fisher's exact test were included in the multivariate logistic regression. Overall, only three variables remained significant. First, participants who never had their blood pressure measured had higher prevalence compared to those who had it checked recently (33.3% vs. 19.1%); odds ratio: 2.24). Secondly, participants who were not aware of the risk of developing hypertension were significantly more likely to have undiagnosed hypertension compared to those who were aware (27.9% vs. 16.7%; odds ratio: 1.81). Lastly, middle-aged participants (30-49 years) and older (50-65 years), were significantly more likely to have undiagnosed hypertension compared to those who were 18-29 years old (30.0% and 23.7% vs. 11.8%; odds ratio: 3.58 and 3.38 vs. 1.00).ConclusionThe prevalence of undiagnosed hypertension could be substantial among Tongan adults, implicating a need to address this issue by doing further research and review current public health work to address hypertension in Tonga. Undiagnosed hypertension was associated with having no experience of blood pressure measurement, lack of awareness about hypertension, and age. Tongan government should provide people with more opportunities to have their blood pressure measured and to improve their awareness.

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Modeled state-level estimates of hypertension prevalence and undiagnosed hypertension among US adults during 2013-2015.

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