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Article ; Online: A multi-step approach to managing missing data in time and patient variant electronic health records.

Cesare, Nina / Were, Lawrence P O

2022 Volume 15, Issue 1, Page(s) 64

Abstract: Objective: Electronic health records (EHR) hold promise for conducting large-scale analyses linking individual characteristics to health outcomes. However, these data often contain a large number of missing values at both the patient and visit level due ...

Abstract	Objective: Electronic health records (EHR) hold promise for conducting large-scale analyses linking individual characteristics to health outcomes. However, these data often contain a large number of missing values at both the patient and visit level due to variation in data collection across facilities, providers, and clinical need. This study proposes a stepwise framework for imputing missing values within a visit-level EHR dataset that combines informative missingness and conditional imputation in a scalable manner that may be parallelized for efficiency. Results: For this study we use a subset of data from AMPATH representing information from 530,812 clinic visits from 16,316 Human Immunodeficiency Virus (HIV) positive women across Western Kenya who have given birth. We apply this process to a set of 84 clinical, social and economic variables and are able to impute values for 84.6% of variables with missing data with an average reduction in missing data of approximately 35.6%. We validate the use of this imputed dataset by predicting National Hospital Insurance Fund (NHIF) enrollment with 94.8% accuracy.
MeSH term(s)	Data Collection ; Electronic Health Records ; Female ; Humans ; Kenya
Language	English
Publishing date	2022-02-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2413336-X
ISSN	1756-0500 ; 1756-0500
ISSN (online)	1756-0500
ISSN	1756-0500
DOI	10.1186/s13104-022-05911-w
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Article ; Online: Handing the Microphone to Women: Changes in Gender Representation in Editorial Contributions Across Medical and Health Journals 2008-2018.

Chang, Angela Y / Cesare, Nina

International journal of health policy and management

2020 Volume 9, Issue 7, Page(s) 269–273

Abstract: The editorial materials in top medical and public health journals are opportunities for experts to offer thoughts that might influence the trajectory of the field. To date, while some studies have examined gender bias in the publication of editorial ... ...

Abstract	The editorial materials in top medical and public health journals are opportunities for experts to offer thoughts that might influence the trajectory of the field. To date, while some studies have examined gender bias in the publication of editorial materials in medical journals, none have studied public health journals. In this perspective, we studied the gender ratio of the editorial materials published in the top health and medical sciences journals between 2008 and early 2018 to test whether gender bias exists. We studied a total of 59 top journals in health and medical sciences. Overall, while there is a trend of increasing proportion of female first authors, there is still a greater proportion of male than female first authors. The average male-to-female first author ratio during the study period across all journals was 2.08. Ensuring equal access and exposure through journal editorials is a critical step, albeit only one step of a longer journey, towards gender balance in health and medical sciences research. Editors of top journals have a key role to play in pushing the fields towards more balanced gender equality, and we strongly urge editors to rethink the strategies for inviting authors for editorial materials.
MeSH term(s)	Authorship ; Female ; Humans ; Male ; Medicine ; Periodicals as Topic ; Sexism
Language	English
Publishing date	2020-07-01
Publishing country	Iran
Document type	Journal Article
ZDB-ID	2724317-5
ISSN	2322-5939 ; 2322-5939
ISSN (online)	2322-5939
ISSN	2322-5939
DOI	10.15171/ijhpm.2020.06
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Article ; Online: Association between wealth, insurance coverage, urban residence, median age and COVID-19 deaths across states in Nigeria.

Akinseinde, Samuel A / Kosemani, Samson / Osuolale, Emmanuel / Cesare, Nina / Pellicane, Samantha / Nsoesie, Elaine O

PloS one

2023 Volume 18, Issue 9, Page(s) e0291118

Abstract: This study measures associations between COVID-19 deaths and sociodemographic factors (wealth, insurance coverage, urban residence, age, state population) for states in Nigeria across two waves of the COVID-19 pandemic: February 27th 2020 to October 24th ...

Abstract	This study measures associations between COVID-19 deaths and sociodemographic factors (wealth, insurance coverage, urban residence, age, state population) for states in Nigeria across two waves of the COVID-19 pandemic: February 27th 2020 to October 24th 2020 and October 25th 2020 to July 25th 2021. Data sources include 2018 Nigeria Demographic and Health Survey and Nigeria Centre for Disease Control (NCDC) COVID-19 daily reports. It uses negative binomial models to model deaths, and stratifies results by respondent gender. It finds that overall mortality rates were concentrated within three states: Lagos, Edo and Federal Capital Territory (FCT) Abuja. Urban residence and insurance coverage are positively associated with differences in deaths for the full sample. The former, however, is significant only during the early stages of the pandemic. Associative differences in gender-stratified models suggest that wealth was a stronger protective factor for men and insurance a stronger protective factor for women. Associative strength between sociodemographic measures and deaths varies by gender and pandemic wave, suggesting that the pandemic impacted men and women in unique ways, and that the effectiveness of interventions should be evaluated for specific waves or periods.
MeSH term(s)	Insurance Coverage ; Urban Population ; COVID-19/mortality ; Humans ; Nigeria/epidemiology ; Sociodemographic Factors ; Age Factors ; Male ; Female
Language	English
Publishing date	2023-09-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0291118
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Article ; Online: Use of machine learning methods to understand discussions of female genital mutilation/cutting on social media.

Babbs, Gray / Weber, Sarah E / Abdalla, Salma M / Cesare, Nina / Nsoesie, Elaine O

PLOS global public health

2023 Volume 3, Issue 7, Page(s) e0000878

Abstract: Female genital mutilation/cutting (FGM/C) describes several procedures that involve injury to the vulva or vagina for nontherapeutic reasons. Though at least 200 million women and girls living in 30 countries have undergone FGM/C, there is a paucity of ... ...

Abstract	Female genital mutilation/cutting (FGM/C) describes several procedures that involve injury to the vulva or vagina for nontherapeutic reasons. Though at least 200 million women and girls living in 30 countries have undergone FGM/C, there is a paucity of studies focused on public perception of FGM/C. We used machine learning methods to characterize discussion of FGM/C on Twitter in English from 2015 to 2020. Twitter has emerged in recent years as a source for seeking and sharing health information and misinformation. We extracted text metadata from user profiles to characterize the individuals and locations involved in conversations about FGM/C. We extracted major discussion themes from posts using correlated topic modeling. Finally, we extracted features from posts and applied random forest models to predict user engagement. The volume of tweets addressing FGM/C remained fairly stable across years. Conversation was mostly concentrated among the United States and United Kingdom through 2017, but shifted to Nigeria and Kenya in 2020. Some of the discussion topics associated with FGM/C across years included Islam, International Day of Zero Tolerance, current news stories, education, activism, male circumcision, human rights, and feminism. Tweet length and follower count were consistently strong predictors of engagement. Our findings suggest that (1) discussion about FGM/C has not evolved significantly over time, (2) the majority of the conversation about FGM/C on English-speaking Twitter is advocating for an end to the practice, (3) supporters of Donald Trump make up a substantial voice in the conversation about FGM/C, and (4) understanding the nuances in how people across cultures refer to and discuss FGM/C could be important for the design of public health communication and intervention.
Language	English
Publishing date	2023-07-25
Publishing country	United States
Document type	Journal Article
ISSN	2767-3375
ISSN (online)	2767-3375
DOI	10.1371/journal.pgph.0000878
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Article ; Online: Modeling health and well-being measures using ZIP code spatial neighborhood patterns.

Jain, Abhi / LaValley, Michael / Dukes, Kimberly / Lane, Kevin / Winter, Michael / Spangler, Keith R / Cesare, Nina / Wang, Biqi / Rickles, Michael / Mohammed, Shariq

Scientific reports

2024 Volume 14, Issue 1, Page(s) 9180

Abstract: Individual-level assessment of health and well-being permits analysis of community well-being and health risk evaluations across several dimensions of health. It also enables comparison and rankings of reported health and well-being for large ... ...

Abstract	Individual-level assessment of health and well-being permits analysis of community well-being and health risk evaluations across several dimensions of health. It also enables comparison and rankings of reported health and well-being for large geographical areas such as states, metropolitan areas, and counties. However, there is large variation in reported well-being within such large spatial units underscoring the importance of analyzing well-being at more granular levels, such as ZIP codes. In this paper, we address this problem by modeling well-being data to generate ZIP code tabulation area (ZCTA)-level rankings through spatially informed statistical modeling. We build regression models for individual-level overall well-being index and scores from five subscales (Physical, Financial, Social, Community, Purpose) using individual-level demographic characteristics as predictors while including a ZCTA-level spatial effect. The ZCTA neighborhood information is incorporated by using a graph Laplacian matrix; this enables estimation of the effect of a ZCTA on well-being using individual-level data from that ZCTA as well as by borrowing information from neighboring ZCTAs. We deploy our model on well-being data for the U.S. states of Massachusetts and Georgia. We find that our model can capture the effects of demographic features while also offering spatial effect estimates for all ZCTAs, including ones with no observations, under certain conditions. These spatial effect estimates provide community health and well-being rankings of ZCTAs, and our method can be deployed more generally to model other outcomes that are spatially dependent as well as data from other states or groups of states.
MeSH term(s)	Humans ; Male ; Female ; Residence Characteristics ; Neighborhood Characteristics ; Adult ; Middle Aged ; Health Status ; Models, Statistical ; Aged
Language	English
Publishing date	2024-04-22
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-024-58157-w
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Article ; Online: COVID-19 Misinformation Spread in Eight Countries: Exponential Growth Modeling Study.

Nsoesie, Elaine Okanyene / Cesare, Nina / Müller, Martin / Ozonoff, Al

Journal of medical Internet research

2020 Volume 22, Issue 12, Page(s) e24425

Abstract: Background: The epidemic of misinformation about COVID-19 transmission, prevention, and treatment has been going on since the start of the pandemic. However, data on the exposure and impact of misinformation is not readily available.: Objective: We ... ...

Abstract	Background: The epidemic of misinformation about COVID-19 transmission, prevention, and treatment has been going on since the start of the pandemic. However, data on the exposure and impact of misinformation is not readily available. Objective: We aim to characterize and compare the start, peak, and doubling time of COVID-19 misinformation topics across 8 countries using an exponential growth model usually employed to study infectious disease epidemics. Methods: COVID-19 misinformation topics were selected from the World Health Organization Mythbusters website. Data representing exposure was obtained from the Google Trends application programming interface for 8 English-speaking countries. Exponential growth models were used in modeling trends for each country. Results: Searches for "coronavirus AND 5G" started at different times but peaked in the same week for 6 countries. Searches for 5G also had the shortest doubling time across all misinformation topics, with the shortest time in Nigeria and South Africa (approximately 4-5 days). Searches for "coronavirus AND ginger" started at the same time (the week of January 19, 2020) for several countries, but peaks were incongruent, and searches did not always grow exponentially after the initial week. Searches for "coronavirus AND sun" had different start times across countries but peaked at the same time for multiple countries. Conclusions: Patterns in the start, peak, and doubling time for "coronavirus AND 5G" were different from the other misinformation topics and were mostly consistent across countries assessed, which might be attributable to a lack of public understanding of 5G technology. Understanding the spread of misinformation, similarities and differences across different contexts can help in the development of appropriate interventions for limiting its impact similar to how we address infectious disease epidemics. Furthermore, the rapid proliferation of misinformation that discourages adherence to public health interventions could be predictive of future increases in disease cases.
MeSH term(s)	COVID-19/epidemiology ; COVID-19/virology ; Communication ; Humans ; Pandemics ; SARS-CoV-2/isolation & purification
Language	English
Publishing date	2020-12-15
Publishing country	Canada
Document type	Journal Article ; Multicenter Study
ZDB-ID	2028830-X
ISSN	1438-8871 ; 1439-4456
ISSN (online)	1438-8871
ISSN	1439-4456
DOI	10.2196/24425
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Article ; Online: Diet during the COVID-19 pandemic: An analysis of Twitter data.

Hernandez, Mark A / Modi, Shagun / Mittal, Kanisha / Dwivedi, Pallavi / Nguyen, Quynh C / Cesare, Nina L / Nsoesie, Elaine O

Patterns (New York, N.Y.)

2022 Volume 3, Issue 8, Page(s) 100547

Abstract: In this study, we measured the association between county characteristics and changes in healthy-food, fast-food, and alcohol tweets during the COVID-19 pandemic in the United States. Our analytic dataset consisted of 1,282,316 geotagged tweets that ... ...

Abstract	In this study, we measured the association between county characteristics and changes in healthy-food, fast-food, and alcohol tweets during the COVID-19 pandemic in the United States. Our analytic dataset consisted of 1,282,316 geotagged tweets that referenced food consumption posted before (63.2%) and during (36.8%) the pandemic and included all US states. We found the share of healthy-food tweets increased by 20.5% during the pandemic compared with pre-pandemic, while fast-food and alcohol tweets decreased by 9.4% and 11.4%, respectively. We also observed that time spent at home and more grocery stores per capita were associated with increased odds of healthy-food tweets and decreased odds of fast-food tweets. More liquor stores per capita was associated with increased odds of alcohol tweets. Our results highlight the potential impact of the pandemic on nutrition and alcohol consumption and the association between the built environment and health behaviors.
Language	English
Publishing date	2022-06-15
Publishing country	United States
Document type	Journal Article
ISSN	2666-3899
ISSN (online)	2666-3899
DOI	10.1016/j.patter.2022.100547
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Article ; Online: Impacts of the choice of distance measurement method on estimates of access to point-based resources.

Nori-Sarma, Amruta / Spangler, Keith R / Wang, Biqi / Cesare, Nina / Dukes, Kimberly A / Lane, Kevin J

Journal of exposure science & environmental epidemiology

2022 Volume 33, Issue 2, Page(s) 237–243

Abstract: Background/objective: Lack of access to resources such as medical facilities and grocery stores is related to poor health outcomes and inequities, particularly in an environmental justice framework. There can be substantial differences in quantifying " ... ...

Abstract	Background/objective: Lack of access to resources such as medical facilities and grocery stores is related to poor health outcomes and inequities, particularly in an environmental justice framework. There can be substantial differences in quantifying "access" to such resources, depending on the geospatial method used to generate distance estimates. Methods: We compared three methods for calculating distance to the nearest grocery store to illustrate differential access at the census block-group level in the Atlanta metropolitan area, including: Euclidean distance estimation, service areas incorporating roadways and other factors, and cost distance for every point on the map. Results: We found notable differences in access across the three estimation techniques, implying a high potential for exposure misclassification by estimation method. There was a lack of nuanced exposure in the highest- and lowest-access areas using the Euclidean distance method. We found an Intraclass Correlation Coefficient (ICC) of 0.69 (0.65, 0.73), indicating moderate agreement between estimation methods. Significance: As compared with Euclidean distance, service areas and cost distance may represent a more meaningful characterization of "access" to resources. Each method has tradeoffs in computational resources required versus potential improvement in exposure classification. Careful consideration of the method used for determining "access" will reduce subsequent misclassifications.
MeSH term(s)	Humans ; Censuses ; Georgia ; Neighborhood Characteristics ; Social Determinants of Health ; Health Status Disparities ; Geography, Medical
Language	English
Publishing date	2022-02-10
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2218551-3
ISSN	1559-064X ; 1559-0631
ISSN (online)	1559-064X
ISSN	1559-0631
DOI	10.1038/s41370-022-00414-z
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Article: Social media captures demographic and regional physical activity.

Cesare, Nina / Nguyen, Quynh C / Grant, Christan / Nsoesie, Elaine O

BMJ open sport & exercise medicine

2019 Volume 5, Issue 1, Page(s) e000567

Abstract: Objectives: We examined the use of data from social media for surveillance of physical activity prevalence in the USA.: Methods: We obtained data from the social media site Twitter from April 2015 to March 2016. The data consisted of 1 382 284 ... ...

Abstract	Objectives: We examined the use of data from social media for surveillance of physical activity prevalence in the USA. Methods: We obtained data from the social media site Twitter from April 2015 to March 2016. The data consisted of 1 382 284 geotagged physical activity tweets from 481 146 users (55.7% men and 44.3% women) in more than 2900 counties. We applied machine learning and statistical modelling to demonstrate sex and regional variations in preferred exercises, and assessed the association between reports of physical activity on Twitter and population-level inactivity prevalence from the US Centers for Disease Control and Prevention. Results: The association between physical inactivity tweet patterns and physical activity prevalence varied by sex and region. Walking was the most popular physical activity for both men and women across all regions (15.94% (95% CI 15.85% to 16.02%) and 18.74% (95% CI 18.64% to 18.88%) of tweets, respectively). Men and women mentioned performing gym-based activities at approximately the same rates (4.68% (95% CI 4.63% to 4.72%) and 4.13% (95% CI 4.08% to 4.18%) of tweets, respectively). CrossFit was most popular among men (14.91% (95% CI 14.52% to 15.31%)) among gym-based tweets, whereas yoga was most popular among women (26.66% (95% CI 26.03% to 27.19%)). Men mentioned engaging in higher intensity activities than women. Overall, counties with higher physical activity tweets also had lower leisure-time physical inactivity prevalence for both sexes. Conclusions: The regional-specific and sex-specific activity patterns captured on Twitter may allow public health officials to identify changes in health behaviours at small geographical scales and to design interventions best suited for specific populations.
Language	English
Publishing date	2019-07-14
Publishing country	England
Document type	Journal Article
ZDB-ID	2817580-3
ISSN	2055-7647
ISSN	2055-7647
DOI	10.1136/bmjsem-2019-000567
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Article: Use of Social Media, Search Queries, and Demographic Data to Assess Obesity Prevalence in the United States.

Cesare, Nina / Dwivedi, Pallavi / Nguyen, Quynh / Nsoesie, Elaine O

Palgrave communications

2019 Volume 5, Issue 1

Abstract: Obesity is a global epidemic affecting millions. Implementation of interventions to curb obesity rates requires timely surveillance. In this study, we estimated sex-specific obesity prevalence using social media, search queries, demographics and built ... ...

Abstract	Obesity is a global epidemic affecting millions. Implementation of interventions to curb obesity rates requires timely surveillance. In this study, we estimated sex-specific obesity prevalence using social media, search queries, demographics and built environment variables. We collected 3,817,125 and 1,382,284 geolocated tweets on food and exercise respectively, from Twitter's streaming API from April 2015 to March 2016. We also obtained searches related to physical activity and diet from Google Search Trends for the same time period. Next, we inferred the gender of Twitter users using machine learning methods and applied mixed-effects state-level linear regression models to estimate obesity prevalence. We observed differences in discussions of physical activity and foods, with males reporting higher intensity physical activities and lower caloric foods across 40 and 48 states, respectively. Additionally, counties with the highest percentage of exercise and food tweets had lower male and female obesity prevalence. Lastly, our models separately captured overall male and female spatial trends in obesity prevalence. The average correlation between actual and estimated obesity prevalence was 0.789 (95% CI, 0.785, 0.786) and 0.830 (95% CI, 0.830, 0.831) for males and females, respectively. Social media can provide timely community-level data on health information seeking and changes in behaviors, sentiments and norms. Social media data can also be combined with other data types such as, demographics, built environment variables, diet and physical activity indicators from other digital sources (e.g., mobile applications and wearables) to monitor health behaviors at different geographic scales, and to supplement delayed estimates from traditional surveillance systems.
Language	English
Publishing date	2019-09-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2807280-7
ISSN	2055-1045
ISSN	2055-1045
DOI	10.1057/s41599-019-0314-x
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