The share of the population with overweight in the United States was forecast to continuously increase between 2024 and 2029 by in total 1.6 percentage points. After the fifteenth consecutive increasing year, the overweight population share is estimated to reach 77.43 percent and therefore a new peak in 2029. Notably, the share of the population with overweight of was continuously increasing over the past years.Overweight is defined as a body mass index (BMI) of more than 25.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the share of the population with overweight in countries like Canada and Mexico.

This is a source dataset for a Let's Get Healthy California indicator at https://letsgethealthy.ca.gov/. This table displays the percentage of adults meeting Aerobic Physical Activity guidelines in California. It contains data for California only. The data are from the California Behavioral Risk Factor Surveillance Survey (BRFSS). The California BRFSS is an annual cross-sectional health-related telephone survey that collects data about California residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. The BRFSS is conducted by the Public Health Survey Research Program of California State University, Sacramento under contract from CDPH. The column percentages are weighted to the 2010 California Department of Finance (DOF) population statistics. Population estimates were obtained from the CA DOF for age, race/ethnicity, and sex. Values may therefore differ from what has been published in the national BRFSS data tables by the Centers for Disease Control and Prevention (CDC) or other federal agencies.

This is a source dataset for a Let's Get Healthy California indicator at "https://letsgethealthy.ca.gov/." This table displays the proportion of adults who were ever told they had a depressive disorder in California. It contains data for California only. The data are from the California Behavioral Risk Factor Surveillance Survey (BRFSS). The California BRFSS is an annual cross-sectional health-related telephone survey that collects data about California residents regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. The BRFSS is conducted by Public Health Survey Research Program of California State University, Sacramento under contract from CDPH. This indicator is based on the question: "“Has a doctor, nurse or other health professional EVER told you that you have a depressive disorder (including depression, major depression, dysthymia, or minor depression)?” NOTE: Denominator data and weighting was taken from the California Department of Finance, not U.S. Census. Values may therefore differ from what has been published in the national BRFSS data tables by the Centers for Disease Control and Prevention (CDC) or other federal agencies.

Dementia can be difficult for married couples for many reasons, including the introduction of caregiving burden, loss of intimacy, and financial strain. In this study, we investigated the impact of dementia staging and neuropsychiatric behavioral symptoms on the likelihood of divorce or separation for older adult married couples. For this case-control study, we used data from the National Alzheimer’s Coordinating Center (NACC) Uniform dataset (UDS) versions 2 and 3. This dataset was from 2007 to 2021 and contains standardized clinical information submitted by NIA/NIH Alzheimer’s Disease Research Centers (ADRCs) across the United States (US). This data was from 37 ADRCs. We selected participants who were married or living as married/domestic partners at their initial visit. Cases were defined by a first divorce/separation occurring during the follow-up period, resulting in 291 participants. We selected 5 controls for each married/living as married case and matched on age. Conditional logistic regression estimated the association between overall Neuro Psychiatric Inventory (NPI) score and severity of individual symptoms of the NPI with case/control status, adjusted for education, the CDR® Dementia Staging Instrument score, living situation, symptom informant, sex, and race. Separate analyses were conducted for each symptom. Multiple comparisons were accounted for with the Hochberg method. Later stage of dementia was negatively associated with divorce/separation with an adjusted odds ratio (AOR) = 0.68 (95%CI = 0.50 to 0.93). A higher overall NPI score was positively associated with divorce/separation AOR = 1.08 (95% CI = 1.03 to 1.12,). More severe ratings of agitation/aggression, depression/dysphoria, disinhibition, and elation/euphoria were associated with greater odds of divorce/separation. Among older adults in the US, a later stage of dementia is associated with a lower likelihood of divorce or separation, while having more severe neuropsychiatric behavioral symptoms of agitation/aggression, depression/dysphoria, disinhibition, and elation/euphoria are associated with a higher likelihood of divorce or separation.

Chronic kidney disease (CKD), which has become a global public health issue, is associated with mitochondrial dysfunction. Niacin is a necessary coenzyme for mitochondrial energy metabolism. However, the association between dietary niacin intake and CKD remains uncertain. This study aimed to investigate the association between dietary niacin intake and CKD in American adults. This is a cross-sectional study. 25,608 individuals aged ≥20 years from the National Health and Nutrition Examination Survey from 2007 to 2018 were involved. Dietary niacin intake was estimated based on 24-hour dietary recalls conducted by trained personnel. CKD was determined by an estimated glomerular filtration rate (eGFR) (

United States US: Mortality Rate Attributed to Household and Ambient Air Pollution: Age-standardized: Male data was reported at 17.000 NA in 2016. United States US: Mortality Rate Attributed to Household and Ambient Air Pollution: Age-standardized: Male data is updated yearly, averaging 17.000 NA from Dec 2016 (Median) to 2016, with 1 observations. United States US: Mortality Rate Attributed to Household and Ambient Air Pollution: Age-standardized: Male 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: Health Statistics. Mortality rate attributed to household and ambient air pollution is the number of deaths attributable to the joint effects of household and ambient air pollution in a year per 100,000 population. The rates are age-standardized. Following diseases are taken into account: acute respiratory infections (estimated for all ages); cerebrovascular diseases in adults (estimated above 25 years); ischaemic heart diseases in adults (estimated above 25 years); chronic obstructive pulmonary disease in adults (estimated above 25 years); and lung cancer in adults (estimated above 25 years).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

This data collection provides information on labor force activity for the week prior to the survey. Comprehensive data are available on the employment status, occupation, and industry of persons 14 years old and over. Also shown are personal characteristics such as age, sex, race, marital status, veteran status, household relationships, educational background, and Spanish origin. Supplemental data provide information on disease history and/or protection through immunization against the common childhood diseases (diphtheria, tetanus, and whooping cough, polio, measles, rubella, chicken pox, and mumps) for persons 0-19 years of age. Data on immunization against influenza and pneumonia are available for all persons. Data are also available for adults on diabetes, chronic kidney disease, and certain chronic heart and lung conditions. Also provided is an indicator for children 0-5 years of age who were enrolled in licensed day care centers during the past year. For persons 16 years old and older who had smoked a minimum of 100 cigarettes, the following data are provided: age first started smoking, if they currently smoke, and whether other tobacco products such as snuff, chewing tobacco, cigars, and pipe tobacco were used. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR09133.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

While previous research has highlighted the potential advantages of increasing dietary fiber intake (DFI) for managing hypertension and chronic kidney disease (CKD), there is a gap in large-scale empirical studies examining the relationship between DFI and CKD among hypertensive and nonhypertensive cohorts independently. This study involved 22,871 participants sourced from the NHANES database spanning 2009 to 2020, who were divided into hypertensive (n = 9,861) and nonhypertensive (n = 13,010) groups. The analysis revealed a significant inverse correlation between DFI and CKD prevalence across the sample after adjusting for various covariates (OR = 0.98, 95% CI: 0.97–0.99, p = 0.001). Within the subset of hypertensive individuals, this inverse association mirrors the findings of the overall sample, indicating that a higher DFI was associated with a reduced occurrence of CKD (OR = 0.97, 95% CI: 0.96–0.99, p 

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

National Alzheimer’s Coordinating Center (NACC) uniform dataset characteristics of cases and controls.