West Virginia, Mississippi, and Arkansas are the U.S. states with the highest percentage of their population who are obese. The states with the lowest percentage of their population who are obese include Colorado, Hawaii, and Massachusetts. Obesity in the United States Obesity is a growing problem in many countries around the world, but the United States has the highest rate of obesity among all OECD countries. The prevalence of obesity in the United States has risen steadily over the previous two decades, with no signs of declining. Obesity in the U.S. is more common among women than men, and overweight and obesity rates are higher among African Americans than any other race or ethnicity. Causes and health impacts Obesity is most commonly the result of a combination of poor diet, overeating, physical inactivity, and a genetic susceptibility. Obesity is associated with various negative health impacts, including an increased risk of cardiovascular diseases, certain types of cancer, and diabetes type 2. As of 2022, around 8.4 percent of the U.S. population had been diagnosed with diabetes. Diabetes is currently the eighth leading cause of death in the United States.
Obesity has become a major concern for health officials in the United States. Rates of obesity are higher than ever before and as a result, consequential medical conditions have arisen in those who suffer from obesity; while at the same time, medical expenses are skyrocketing for these same individuals. In this study, I analyze regional trends in the United States of both obesity rates and walkability in 74 cities in the United States. After analyzing the data and constructing visual representations, I found that the Northeast region of the US is most walkable, while the Southeast and Southwestern regions are the least walkable. In regards to obesity rates, I found that the West had the lowest obesity rates in both 2010 and 2013, while the Midwest and the Southeast had a high obesity rate in both 2010 and 2013. Additionally, the Northeastern US had a high obesity rate in 2013.
This statistic shows the jobs in the U.S. with the lowest percentage of employees who were overweight or obese as of 2015. It was found that only **** percent of waiters or bartenders were overweight and only **** percent were obese.
In 2022, the U.S. states with the highest rates of obesity among women were Tennessee, Louisiana, and Mississippi. At that time, almost ** percent of women in Tennessee were considered obese. The states with the highest rates of obesity among men are West Virginia, Arkansas, and Oklahoma. Obesity: Women vs. men As of 2023, women in the United States had slightly higher rates of obesity than men. At that time, around **** percent of women were considered obese, compared to **** percent of men. Rates of obesity among both men and women are higher in the United States than any other OECD country, with high-calorie diets, often from fast food and sugary drinks, and large food portion sizes being partly to blame. In 2024, the mean self-reported weight among men in the United States was *** pounds, while women reported weighing an average of *** pounds. Which state is the most obese? As of 2023, West Virginia had the highest prevalence of adult obesity in the United States, with around ** percent of the population considered obese. Following West Virginia, Mississippi, Arkansas, and Louisiana, had some of the highest rates of obesity in the country. Colorado had the lowest share of adults who were obese at that time, but still, ********* of adults in the state were obese. West Virginia is also the state with the highest prevalence of obesity among high school students, with ** percent of high schoolers considered obese in 2021. Obesity in childhood is associated with obesity as adults, as well as mental health problems such as anxiety and depression.
Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically
The adult obesity rate, or the percentage of the county population (age 18 and older*) that is obese, or has a Body Mass Index (BMI) equal to or greater than 30 [kg/m2], is illustrative of a serious health problem, in Champaign County, statewide, and nationally.
The adult obesity rate data shown here spans from Reporting Years (RY) 2015 to 2024. Champaign County’s adult obesity rate fluctuated during this time, peaking in RY 2022. The adult obesity rates for Champaign County, Illinois, and the United States were all above 30% in RY 2024, but the Champaign County rate was lower than the state and national rates. All counties in Illinois had an adult obesity rate above 30% in RY 2024, but Champaign County's rate is one of the lowest among all Illinois counties.
Obesity is a health problem in and of itself, and is commonly known to exacerbate other health problems. It is included in our set of indicators because it can be easily measured and compared between Champaign County and other areas.
This data was sourced from the University of Wisconsin’s Population Health Institute’s and the Robert Wood Johnson Foundation’s County Health Rankings & Roadmaps. Each year’s County Health Rankings uses data from the most recent previous years that data is available. Therefore, the 2024 County Health Rankings (“Reporting Year” in the table) uses data from 2021 (“Data Year” in the table). The survey methodology changed in Reporting Year 2015 for Data Year 2011, which is why the historical data shown here begins at that time. No data is available for Data Year 2018. The County Health Rankings website notes to use caution if comparing RY 2024 data with prior years.
*The percentage of the county population measured for obesity was age 20 and older through Reporting Year 2021, but starting in Reporting Year 2022 the percentage of the county population measured for obesity was age 18 and older.
Source: University of Wisconsin Population Health Institute. County Health Rankings & Roadmaps 2024. www.countyhealthrankings.org.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States US: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 data was reported at 6.900 % in 2012. This records an increase from the previous number of 6.400 % for 2009. United States US: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 data is updated yearly, averaging 6.900 % from Dec 1991 (Median) to 2012, with 6 observations. The data reached an all-time high of 8.700 % in 2005 and a record low of 5.100 % in 1991. United States US: Prevalence of Overweight: Weight for Height: Female: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Prevalence of overweight, female, is the percentage of girls under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's new child growth standards released in 2006.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Estimates of overweight children are also from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues
In 2022, over ** percent of both men and women in the United States reported themselves as obese (BMI over 30), making it the country with the highest percentage of obese adults on this list. Other selected countries on the list with a high prevalence of obesity among adults included the United Kingdom and Australia. Obesity groups in the United States In 2023, Black adults had the highest overweight and obesity rates of any race or ethnicity in the United States. Asians and Native Hawaiians or Pacific Islanders had the lowest rates by far, with roughly ** percent. In 2022, almost ** percent of people aged 65 and older were obese in the United States. This estimate has been steadily increasing since 2013 when roughly ** percent of elderly Americans were obese. Leading health problems worldwide Obesity was considered one of 2024’s biggest health problems: ** percent of adults worldwide stated that obesity was the biggest health issue for people within their country. Around ** percent of adults stated that mental health was the most significant problem facing their country that year.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States Prevalence of Overweight: % of Adults data was reported at 67.900 % in 2016. This records an increase from the previous number of 67.400 % for 2015. United States Prevalence of Overweight: % of Adults data is updated yearly, averaging 55.200 % from Dec 1975 (Median) to 2016, with 42 observations. The data reached an all-time high of 67.900 % in 2016 and a record low of 41.000 % in 1975. United States Prevalence of Overweight: % of Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Social: Health Statistics. Prevalence of overweight adults is the percentage of adults ages 18 and over whose Body Mass Index (BMI) is more than 25 kg/m2. Body Mass Index (BMI) is a simple index of weight-for-height, or the weight in kilograms divided by the square of the height in meters.;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;;
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States US: Prevalence of Overweight: Weight for Height: % of Children Under 5 data was reported at 6.000 % in 2012. This records a decrease from the previous number of 7.800 % for 2009. United States US: Prevalence of Overweight: Weight for Height: % of Children Under 5 data is updated yearly, averaging 7.000 % from Dec 1991 (Median) to 2012, with 5 observations. The data reached an all-time high of 8.100 % in 2005 and a record low of 5.400 % in 1991. United States US: Prevalence of Overweight: Weight for Height: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's new child growth standards released in 2006.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; Linear mixed-effect model estimates; Estimates of overweight children are also from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues
https://www.icpsr.umich.edu/web/ICPSR/studies/34974/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/34974/terms
Nearly 9 million Americans live in extreme-poverty neighborhoods, places that also tend to be racially segregated and dangerous. Yet, the effects on the well-being of residents of moving out of such communities into less distressed areas remain uncertain. Moving to Opportunity (MTO) is a randomized housing experiment administered by the United States Department of Housing and Urban Development that gave low-income families living in high-poverty areas in five cities the chance to move to lower-poverty areas. Families were randomly assigned to one of three groups: (1) the low-poverty voucher (LPV) group (also called the experimental group) received Section 8 rental assistance certificates or vouchers that they could use only in census tracts with 1990 poverty rates below 10 percent. The families received mobility counseling and help in leasing a new unit. One year after relocating, families could use their voucher to move again if they wished, without any special constraints on location; (2) the traditional voucher (TRV) group (also called the Section 8 group) received regular Section 8 certificates or vouchers that they could use anywhere; these families received no special mobility counseling; (3) the control group received no certificates or vouchers through MTO, but continued to be eligible for project-based housing assistance and whatever other social programs and services to which they would otherwise be entitled. Families were tracked from baseline (1994-1998) through the long-term evaluation survey fielding period (2008-2010) with the purpose of determining the effects of "neighborhood" on participating families. This data collection includes data from the 3,273 adult interviews completed as part of the MTO long-term evaluation. Using data from the long-term evaluation, the associated article reports that moving from a high-poverty to lower-poverty neighborhood was associated in the long-term (10 to 15 years) with modest, but potentially important, reductions in the prevalence of extreme obesity and diabetes. The data contain all outcomes and mediators analyzed for the associated article (with the exception of a few mediator variables from the interim MTO evaluation) as well as a variety of demographic and other baseline measures that were controlled for in the analysis.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
BackgroundUnderstanding the social environmental around obesity has been limited by available data. One promising approach used to bridge similar gaps elsewhere is to use passively generated digital data.PurposeThis article explores the relationship between online social environment via web-based social networks and population obesity prevalence.MethodsWe performed a cross-sectional study using linear regression and cross validation to measure the relationship and predictive performance of user interests on the online social network Facebook to obesity prevalence in metros across the United States of America (USA) and neighborhoods within New York City (NYC). The outcomes, proportion of obese and/or overweight population in USA metros and NYC neighborhoods, were obtained via the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance and NYC EpiQuery systems. Predictors were geographically specific proportion of users with activity-related and sedentary-related interests on Facebook.ResultsHigher proportion of the population with activity-related interests on Facebook was associated with a significant 12.0% (95% Confidence Interval (CI) 11.9 to 12.1) lower predicted prevalence of obese and/or overweight people across USA metros and 7.2% (95% CI: 6.8 to 7.7) across NYC neighborhoods. Conversely, greater proportion of the population with interest in television was associated with higher prevalence of obese and/or overweight people of 3.9% (95% CI: 3.7 to 4.0) (USA) and 27.5% (95% CI: 27.1 to 27.9, significant) (NYC). For activity-interests and national obesity outcomes, the average root mean square prediction error from 10-fold cross validation was comparable to the average root mean square error of a model developed using the entire data set.ConclusionsActivity-related interests across the USA and sedentary-related interests across NYC were significantly associated with obesity prevalence. Further research is needed to understand how the online social environment relates to health outcomes and how it can be used to identify or target interventions.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Abstract Introduction: Cross-national comparison suggests that the timing of the obesity epidemic differs across socio-economic groups (SEGs). Similar to the smoking epidemic, these differences might be described by the diffusion of innovations theory, which states that health behaviours diffuse from higher to lower SEGs. However, the applicability of the diffusion of innovations theory to long-term time trends in obesity by SEG is unknown. We studied long-term trends in the obesity prevalence by socio-economic group in England, France, Finland, Italy, Norway, and the USA and examined whether trends are described by the diffusion of innovations theory. Methods: Obesity prevalence from 1978 to 2019 by educational level, sex, and age group (25+) from health surveys were harmonised, age-standardised, Loess-smoothed, and visualised. Prevalence rate differences were calculated and segmented regression was performed to obtain annual percentage changes, which were compared over time and across SEGs. Results: Obesity prevalence among lower educated has exceeded that of higher educated groups, except among USA men, in all countries throughout the study period. A comparable increase across educational levels was observed until approximately 2000. Recently, obesity prevalence stagnated among higher educated groups in Finland, France, Italy, and Norway, and lower educated groups in England and the USA. Discussion: Recent trends in obesity prevalence by SEG are mostly in line with the diffusion of innovations theory, however, no diffusion from higher to lower SEGs at the start of the epidemic was found. The stagnation among higher SEGs but not lower SEGs suggests that the latter will likely experience the greatest future burden.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
State of Palestine (West Bank and Gaza) PS: Prevalence of Overweight: Weight for Height: % of Children Under 5: Female data was reported at 4.600 % in 2010. This records a decrease from the previous number of 9.400 % for 2007. State of Palestine (West Bank and Gaza) PS: Prevalence of Overweight: Weight for Height: % of Children Under 5: Female data is updated yearly, averaging 7.000 % from Dec 2007 (Median) to 2010, with 2 observations. The data reached an all-time high of 9.400 % in 2007 and a record low of 4.600 % in 2010. State of Palestine (West Bank and Gaza) PS: Prevalence of Overweight: Weight for Height: % of Children Under 5: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Health Statistics. Prevalence of overweight, female, is the percentage of girls under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's new child growth standards released in 2006.; ; World Health Organization, Global Database on Child Growth and Malnutrition. Country-level data are unadjusted data from national surveys, and thus may not be comparable across countries.; Linear mixed-effect model estimates; Estimates of overweight children are also from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
BackgroundObesity, particularly in high-risk groups for food addiction, adversely impacts the brain’s functional characteristics. However, its underlying neurobiological and molecular mechanisms remain elusive. The current study adopted a data-driven approach to investigate obesity-associated intrinsic functional architecture and neurotransmitter receptor patterns.MethodsResting-state fMRI data were acquired from 198 obese and 291 healthy weight individuals from the Human Connectome Project. Intrinsic connectivity contrast (ICC) and fractional amplitude of low-frequency fluctuations (fALFF) analyses were performed to identify the common altered brain regions and then seeds to whole brain functional connectivity (FC) analyses were conducted to determine obesity-related FC features. Additionally, the relationship between intrinsic functional characteristics and molecular imaging features was assessed to examine neurotransmitter-receptor distribution patterns underlying obesity.ResultsObese individuals, compared to healthy weight individuals, showed aberrant ICC and fALFF in both the right dorsolateral prefrontal cortex (DLPFC) and left insula. For the FC results, the obese group displayed increased FC between the right DLPFC and precuneus, left insula and left inferior parietal lobule, right DLPFC as well as decreased FC between right DLPFC and left precentral, left postcentral gyrus, and bilateral paracentral lobule. Additionally, the fALFF alterations in insula/temploral pole and also the rDLPFC-PCL FC partially mediated the relationship between body mass index and the executive function. Furthermore, cross-modal correlation analyses indicated that ICC and fALFF alterations were related to noradrenaline transporter and dopamine receptor distributions, respectively.DiscussionTogether our findings suggested that obesity is associated with atypical neurotransmitter systems and dysfunctional architecture especially in the prefrontal cortex, insula, sensorimotor cortex, and default mode circuits. These may deepen our understanding the neurobiological basis of obesity and provide novel insights into neuroimaging-based treatment and intervention.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
ObjectiveRelaxed natural selection, measured by Biological State Index (Ibs), results in unfavourable genes/mutations accumulation in population. Obesity is partly heritable. We aim to examine and compare the effects of relaxed natural selection on male and female obesity prevalence.MethodsData for 191 countries of the world were captured for this ecological study. Curvilinear regressions, bivariate and partial correlations, linear mixed models and multivariate linear regression analyses were used to examine the relationship between Ibs and sex-specific obesity prevalence. Per capita GDP, urbanization and caloric intake were controlled for as the confounding factors. Fisher r-to-z transformation, R2 increment in multivariate regression and F-test were used to compare the correlations.ResultsCurvilinear regressions, bivariate and partial correlations (controlled for GDP, urbanization and calories) revealed that Ibs was significantly correlated to obesity prevalence of both sexes, but significantly stronger to male than to female obesity prevalence. Curvilinear regression models also showed strong correlations. Mixed linear models, with effects of GDP, urbanisation and caloric intake controlled for, showed that male and female average obesity prevalence rates were significantly higher in countries with greater Ibs value than their equivalents in countries with lower Ibs. Between higher and lower Ibs countries, the gap of male obesity prevalence is 60% greater than the gap of female obesity prevalence. Stepwise multiple regression identified that Ibs was a significant predictor of obesity prevalence of both sexes. Multivariate regression showed that, adding Ibs as an obesity predictor, R2 increment in male model was significantly greater than in female model.ConclusionsRelaxed natural selection may drive males and females to accumulate metabolic faulty genes equally. Probably due to greater environmental, personal intervention in regulating female body mass, relaxed natural selection shows less contributing effects to female obesity prevalence than to male obesity prevalence. Gene therapy to prevent obesity may need to be also taken into account.
In 2023, around ** percent of all adult Hispanics in Texas were obese. In the United States, processed foods are often cheaper than fresh foods, which can impact those with lower income and lead to more weight gain. This statistic depicts the obesity rates for adults in Texas in 2023, by race/ethnicity.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
State of Palestine (West Bank and Gaza) PS: Prevalence of Overweight: Weight for Height: % of Children Under 5 data was reported at 8.200 % in 2014. This records an increase from the previous number of 5.300 % for 2010. State of Palestine (West Bank and Gaza) PS: Prevalence of Overweight: Weight for Height: % of Children Under 5 data is updated yearly, averaging 6.750 % from Dec 1996 (Median) to 2014, with 4 observations. The data reached an all-time high of 11.400 % in 2007 and a record low of 4.000 % in 1996. State of Palestine (West Bank and Gaza) PS: Prevalence of Overweight: Weight for Height: % of Children Under 5 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s State of Palestine (West Bank and Gaza) – Table PS.World Bank.WDI: Health Statistics. Prevalence of overweight children is the percentage of children under age 5 whose weight for height is more than two standard deviations above the median for the international reference population of the corresponding age as established by the WHO's new child growth standards released in 2006.; ; UNICEF, WHO, World Bank: Joint child malnutrition estimates (JME). Aggregation is based on UNICEF, WHO, and the World Bank harmonized dataset (adjusted, comparable data) and methodology.; Linear mixed-effect model estimates; Estimates of overweight children are also from national survey data. Once considered only a high-income economy problem, overweight children have become a growing concern in developing countries. Research shows an association between childhood obesity and a high prevalence of diabetes, respiratory disease, high blood pressure, and psychosocial and orthopedic disorders (de Onis and Blössner 2003). Childhood obesity is associated with a higher chance of obesity, premature death, and disability in adulthood. In addition to increased future risks, obese children experience breathing difficulties and increased risk of fractures, hypertension, early markers of cardiovascular disease, insulin resistance, and psychological effects. Children in low- and middle-income countries are more vulnerable to inadequate nutrition before birth and in infancy and early childhood. Many of these children are exposed to high-fat, high-sugar, high-salt, calorie-dense, micronutrient-poor foods, which tend be lower in cost than more nutritious foods. These dietary patterns, in conjunction with low levels of physical activity, result in sharp increases in childhood obesity, while under-nutrition continues
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The association between obesity (body mass index (BMI) ≥ 30 kg/m2) and pattern of medication use during pregnancy in the United States is not well-studied. Higher pre-pregnancy BMI may be associated with increases or decreases in medication use across pregnancy as symptoms (e.g. reflux) or comorbidities (e.g. gestational diabetes) requiring treatment that may be associated with higher BMI could also change with advancing gestation. To determine whether prenatal medication use, by the number and types of medications, varies by pre-pregnancy obesity status. In a secondary data analysis of a racially/ethnically diverse prospective cohort of pregnant women with low risk for fetal abnormalities enrolled in the first trimester of pregnancy and followed to delivery (singleton, 12 United States clinical sites), free text medication data were obtained at enrollment and up to five follow-up visits and abstracted from medical records at delivery. In 436 women with obesity and 1750 women without obesity (pre-pregnancy BMI, 19–29.9 kg/m2), more than 70% of pregnant women (77% of women with and 73% of women without obesity) reported taking at least one medication during pregnancy, respectively (adjusted risk ratio (aRR)=1.10, 95% confidence interval (CI)=1.01, 1.20), with 81% reporting two and 69% reporting three or more. A total of 17 classes of medications were identified. Among medication classes consumed by at least 5% of all women, the only class that differed between women with and without obesity was hormones and synthetic substitutes (including steroids, progesterone, diabetes, and thyroid medications) in which women with obesity took more medications (11 vs. 5%, aRR = 1.9, 95% CI = 1.38, 2.61) compared to women without obesity. Within this class, a higher percentage of women with obesity took diabetes medications (2.3 vs. 0.7%) and progesterone (3.4 vs. 1.3%) than their non-obese counterparts. Similar percentages of women with and without obesity reported consuming medications in the remaining medication classes including central nervous system agents (50 and 46%), gastrointestinal drugs (43 and 40%), anti-infective agents (23 and 21%), antihistamines (20 and 17%), autonomic drugs (10 and 9%), and respiratory tract agents (7 and 6%), respectively (p > 0.05 for all adjusted comparisons). There were no differences in medication use by obesity status across gestation. Since the study exclusion criteria limited the non-obese group to women without thyroid disease, in a sensitivity analysis we excluded all women who reported thyroid medication intake and still a higher proportion of women with obesity took the hormones and synthetic substitutes class compared to women without obesity. Our findings suggest that pre-pregnancy obesity in otherwise healthy women is associated with a higher use of only selected medications (such as diabetes medications and progesterone) during pregnancy, while the intake of other more common medication types such as analgesics, antibiotics, and antacids does not vary by pre-pregnancy obesity status. As medication safety information for prenatal consumption is insufficient for many medications, these findings highlight the need for a more in-depth examination of factors associated with prenatal medication use.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Number of domains preempted within each state, 2018.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Obesity causes insulin resistance (IR) through systemic low-grade inflammation and can lead to type 2 diabetes mellitus (T2DM). However, the mechanisms that cause IR and T2DM in non-obese individuals are unclear. The Goto-Kakizaki (GK) rat develops IR spontaneously and is a model of non-obese T2DM. These rats exhibit hyperglycemia beginning at weaning and exhibit lower body mass than control Wistar rats. Herein, we tested the hypothesis that macrophages of GK rats are permanently in a pro-inflammatory state, which may be associated with a systemic inflammation condition that mimics the pathogenesis of obesity-induced T2DM. Using eighteen-week-old GK and control Wistar rats, we investigated the proportions of M1 (pro-inflammatory) and M2 (anti-inflammatory) macrophages isolated from the peritoneal cavity. Additionally, the production of inflammatory cytokine and reactive oxygen species (ROS) in cultured macrophages under basal and stimulated conditions was assessed. It was found that phorbol myristate acetate (PMA) stimulation increased GK rat macrophage ROS production by 90-fold compared to basal levels. This response was also three times more pronounced than in control cells (36-fold). The production of pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α), tended to be upregulated in cultured macrophages from GK rats under basal conditions. Macrophages from GK rats produced 1.6 times more granulocyte-macrophage colony-stimulating factor (GM-CSF), 1.5 times more monocyte chemoattractant protein-1 (MCP-1) and 3.3 times more TNF-α than control cells when stimulated with lipopolysaccharide (LPS) (p = 0.0033; p = 0.049; p = 0.002, respectively). Moreover, compared to control cells, GK rats had 60% more M1 (p = 0.0008) and 23% less M2 (p = 0.038) macrophages. This study is the first to report macrophage inflammatory reprogramming towards a pro-inflammatory state in GK rats.
West Virginia, Mississippi, and Arkansas are the U.S. states with the highest percentage of their population who are obese. The states with the lowest percentage of their population who are obese include Colorado, Hawaii, and Massachusetts. Obesity in the United States Obesity is a growing problem in many countries around the world, but the United States has the highest rate of obesity among all OECD countries. The prevalence of obesity in the United States has risen steadily over the previous two decades, with no signs of declining. Obesity in the U.S. is more common among women than men, and overweight and obesity rates are higher among African Americans than any other race or ethnicity. Causes and health impacts Obesity is most commonly the result of a combination of poor diet, overeating, physical inactivity, and a genetic susceptibility. Obesity is associated with various negative health impacts, including an increased risk of cardiovascular diseases, certain types of cancer, and diabetes type 2. As of 2022, around 8.4 percent of the U.S. population had been diagnosed with diabetes. Diabetes is currently the eighth leading cause of death in the United States.