In 2024, around 16 percent of U.S. women reported weighing 200 pounds or more. This statistic shows the average self-reported weight among U.S. women from 1990 to 2024.

This statistic depicts the average body weight of U.S. females aged 20 years and over from 1999 to 2016, by age. According to the data, the average female body weight for those aged 40-59 years was 169.4 in 1999-2000 and increased to 176.4 as of 2015-2016.

This statistic depicts the average body weight of U.S. females aged 20 years and over from 1999 to 2016, by ethnicity. According to the data, the average female body weight for those that identified as non-Hispanic white has increased from ***** in ********* to ***** in *********.

In 2024, the mean average weight reported by men was 195 pounds, while the mean average weight for women was 164 pounds. This statistic shows the mean self-reported weight among U.S. adults from 1990 to 2024, by gender, in pounds.

Surveys in which U.S. adults report their current weight have shown that the share of those reporting they weigh 200 pounds or more has increased over the past few decades. In 2024, around 28 percent of respondents reported their weight as 200 pounds or more, compared to 15 percent in 1990. However, the same surveys show the share of respondents who report they are overweight has decreased compared to figures from 1990. What percentage of the U.S. population is obese? Obesity is an increasing problem in the United States that is expected to become worse in the coming decades. As of 2023, around one third of adults in the United States were considered obese. Obesity is slightly more prevalent among women in the United States, and rates of obesity differ greatly by region and state. For example, in West Virginia, around 41 percent of adults are obese, compared to 25 percent in Colorado. However, although Colorado is the state with the lowest prevalence of obesity among adults, a quarter of the adult population being obese is still shockingly high. The health impacts of being obese Obesity increases the risk of developing a number of health conditions including high blood pressure, heart disease, type 2 diabetes, and certain types of cancer. It is no coincidence that the states with the highest rates of hypertension are also among the states with the highest prevalence of obesity. West Virginia currently has the third highest rate of hypertension in the U.S. with 45 percent of adults with the condition. It is also no coincidence that as rates of obesity in the United States have increased so have rates of diabetes. As of 2022, around 8.4 percent of adults in the United States had been diagnosed with diabetes, compared to six percent in the year 2000. Obesity can be prevented through a healthy diet and regular exercise, which also increases overall health and longevity.

Data on overweight and obesity among adults aged 20 and over in the United States, by selected characteristics, including sex, age, race, Hispanic origin, and poverty level. Data are from Health, United States. SOURCE: National Center for Health Statistics, National Health and Nutrition Examination Survey. Search, visualize, and download these and other estimates from over 120 health topics with the NCHS Data Query System (DQS), available from: https://www.cdc.gov/nchs/dataquery/index.htm.

This statistic depicts the average body weight of U.S. adults aged 20 years and over from 1999 to 2016. According to the data, the average male body weight has increased from 189.4 in 1999-2000 to 197.9 in 2015-2016.

From 2019 to 2021, obesity among pregnant women in the United States was highest among American Indian and Alaska Native women and Black women. This statistic depicts the percentage of pregnant women in the United States from 2019 to 2021 who were obese, overweight, normal weight, or underweight, by race/ethnicity.

In 2022, the U.S. states with the highest rates of obesity among women were Tennessee, Louisiana, and Mississippi. At that time, almost 43 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 33.5 percent of women were considered obese, compared to 32.1 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 195 pounds, while women reported weighing an average of 164 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 41 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, a quarter of adults in the state were obese. West Virginia is also the state with the highest prevalence of obesity among high school students, with 27 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.

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.

The global healthy weight management market is projected to witness a CAGR of XX% over the forecast period (2025-2033), reaching a market value of XXX million by 2033. The market growth is driven by the rising prevalence of obesity and overweight individuals, increasing awareness about the importance of maintaining a healthy weight, and growing disposable income. Key market drivers include increasing health consciousness, the rising popularity of weight loss supplements and diet plans, and the growing demand for personalized weight management solutions. The market is segmented based on application (men, women), type (weight loss diet, physical activity and exercise, medical intervention, others), and region (North America, South America, Europe, Middle East & Africa, Asia Pacific). The weight loss diet segment is expected to dominate the market over the forecast period, owing to the increasing popularity of low-calorie and low-fat diets. The medical intervention segment is projected to witness significant growth, driven by the rising demand for surgical and non-surgical weight loss procedures. Regionally, North America is anticipated to hold a major share of the market, followed by Europe and Asia Pacific. Key market competitors include WW International, Herbalife, Planet Fitness, Nutrisystem, Kellogg, Medifast, Jenny Craig, Johnson Health Tech, Atkins, Technogym, Slimming World, Town Sports, Gold's Gym, Core Health & Fitness, and PureGym, among others.

This statistic depicts the average body weight of U.S. men aged 20 years and over from 1999 to 2016, by ethnicity. According to the data, the average male body weight for those that identified as non-Hispanic white has increased from 192.3 in 1999-2000 to 202.2 in 2015-2016.

BackgroundSuboptimal weight gain during pregnancy is a potentially modifiable risk factor. We aimed to investigate the association between suboptimal gestational weight gain and severe adverse birth outcomes by pre-pregnancy body mass index (BMI) categories, including obesity class I to III.Methods and findingsWe conducted a population-based study of pregnant women with singleton hospital births in Washington State, US, between 2004 and 2013. Optimal, low, and excess weight gain in each BMI category was calculated based on weight gain by gestational age as recommended by the American College of Obstetricians and Gynecologists and the Institute of Medicine. Primary composite outcomes were (1) maternal death and/or severe maternal morbidity (SMM) and (2) perinatal death and/or severe neonatal morbidity. Logistic regression was used to obtain adjusted odds ratios (AORs) and 95% confidence intervals. Overall, 722,839 women with information on pre-pregnancy BMI were included. Of these, 3.1% of women were underweight, 48.1% had normal pre-pregnancy BMI, 25.8% were overweight, and 23.0% were obese. Only 31.5% of women achieved optimal gestational weight gain. Women who had low weight gain were more likely to be African American and have Medicaid health insurance, while women with excess weight gain were more likely to be non-Hispanic white and younger than women with optimal weight gain in each pre-pregnancy BMI category. Compared with women who had optimal weight gain, those with low gestational weight gain had a higher rate of maternal death, 7.97 versus 2.63 per 100,000 (p = 0.027). In addition, low weight gain was associated with the composite adverse maternal outcome (death/SMM) in women with normal pre-pregnancy BMI and in overweight women (AOR 1.12, 95% CI 1.04–1.21, p = 0.004, and AOR 1.17, 95% CI 1.04–1.32, p = 0.009, respectively) compared to women in the same pre-pregnancy BMI category who had optimal weight gain. Similarly, excess gestational weight gain was associated with increased rates of death/SMM among women with normal pre-pregnancy BMI (AOR 1.20, 95% CI 1.12–1.28, p < 0.001) and obese women (AOR 1.12, 95% CI 1.01–1.23, p = 0.019). Low gestational weight gain was associated with perinatal death and severe neonatal morbidity regardless of pre-pregnancy BMI, including obesity classes I, II, and III, while excess weight gain was associated with severe neonatal morbidity only in women who were underweight or had normal BMI prior to pregnancy. Study limitations include the ascertainment of pre-pregnancy BMI using self-report, and lack of data availability for the most recent years.ConclusionsIn this study, we found that most women do not achieve optimal weight gain during pregnancy. Low weight gain was associated with increased risk of severe adverse birth outcomes, and in particular with maternal death and perinatal death. Excess gestational weight gain was associated with severe adverse birth outcomes, except for women who were overweight prior to pregnancy. Weight gain recommendations for this group may need to be reassessed. It is important to counsel women during pregnancy about specific risks associated with both low and excess weight gain.

ContextWhether a healthy lifestyle may be associated with longer telomere length is largely unknown. ObjectivesTo examine healthy lifestyle practices, which are primary prevention measures against major age-related chronic diseases, in relation to leukocyte telomere length. Design and SettingCross-sectional analysis in the Nurses' Health Study (NHS). ParticipantsThe population consisted of 5,862 women who participated in multiple prospective case-control studies within the NHS cohort. Z scores of leukocyte telomere length were derived within each case-control study. Based on prior work, we defined low-risk or healthy categories for five major modifiable factors assessed in 1988 or 1990: non-current smoking, maintaining a healthy body weight (body mass index in 18.5–24.9 kg/m2), engaging in regular moderate or vigorous physical activities (≥150 minutes/week), drinking alcohol in moderation (1 drink/week to

Maternal obesity has been associated with a higher risk of pregnancy-related complications in mothers and offspring; however, effective interventions have not yet been developed. We tested two common interventions, calorie restriction and pravastatin administration, during pregnancy in a rhesus macaque model with the hypothesis that these interventions would normalize metabolic dysregulation in pregnant mothers leading to an improvement in infant metabolic and cognitive/social development. A total of 19 obese mothers were assigned to either one of the two intervention groups (n=5 for calorie restriction; n=7 for pravastatin) or an obese control group (n=7) with no intervention, and maternal gestational samples and postnatal infant samples were compared with lean control mothers (n=6). Gestational calorie restriction normalized one-carbon metabolism dysregulation in obese mothers but altered energy metabolism in their offspring. Although administration of pravastatin during pregnancy tended to normalize blood cholesterol in the mothers, it potentially impacted the gut microbiome and kidney function of their offspring. In the offspring, both calorie restriction and pravastatin administration during pregnancy tended to normalize the activity of AMPK in the brain at 6 months, and while results of the Visual Paired-Comparison test, which measures infant recognition memory, were not significantly impacted by either of the interventions, gestational pravastatin administration, but not calorie restriction, tended to normalize anxiety assessed by the Human Intruder test. Although the two interventions tested in a non-human primate model led to some improvements in metabolism and/or infant brain development, negative impacts were also found in both mothers and infants. Our study emphasizes the importance of assessing gestational interventions for maternal obesity on both maternal and offspring long-term outcomes. Methods Study population Pregnant female rhesus macaques (Macaca mulatta) from an indoor breeding colony at the California National Primate Research Center with appropriate social behavior and previous successful pregnancies were enrolled. Animal handling was approved by the UC Davis Institutional Animal Care and Use Committee (IACUC) (#19299). A qualitative real-time PCR assay (Jimenez & Tarantal, 2003) was used to identify mothers with male fetuses to include in this study. Since obesity is defined as subjects with body fat above 30% for women, according to guidelines from the American Society of Bariatric Physicians, American Medical Association, and in some publications (Okorodudu et al., 2010; Shah & Braverman, 2012), a Body Condition Score (BCS) of 3.5 (32.8 % body fat on average (Summers et al., 2012)) was used as the cutoff. Therefore, mothers with BCS of 3.5 and above were categorized as obese. Obese mothers were randomly assigned to the Obese Control (OC) group, OR group (received calorie Restriction), or OP group (received Pravastatin). Mothers with BCS of 2.5 and below were assigned to the Lean Control (LC) group. The unbalanced sample size was because some mothers were removed from the analyses due to fetal deaths for unknown reasons, misidentification of a female fetus, different timing for study enrollment, or technical issues upon collecting samples. The number of animals was six for the LC, seven for the OC, five for the OR, and seven for the OP groups. Feeding, rearing, and interventions Adult female animals were provided monkey diet (High Protein Primate Diet Jumbo #5047; LabDiet, St. Louis, MO, USA) twice a day between 6–9 am and 1–3 pm. The calories were provided as 56% from carbohydrates, 30% from protein, and 13% from. Mothers in the LC, OC, and OP groups were fed nine biscuits twice a day once pregnancy was confirmed. Mothers in the OR group received a restricted supply of food once the pregnancy was detected and was maintained throughout pregnancy. The food restriction was set such that the average total weight increase would be 8% body weight from the last day before conception because the recommended total weight gain in the 2nd and 3rd trimesters is 5-9 kg for the average US woman with obesity who weighs 80 kg and is 1.6 m in height (Body Mass Index of 30), according to the Institute of Medicine 2009 guidelines (Institute of Medicine and National Research Council, 2009). During nursing of infants older than 4 months, all mothers were provided twelve biscuits. Fresh produce was provided biweekly, and water was provided ad libitum for all mothers. Mothers in the OP group were given pravastatin sodium (ApexBio Technology, Houston, TX, USA) at 20 mg/kg body weight prepared in a neutralized syrup (20 mg/mL sodium bicarbonate dissolved in a fruit-flavored syrup (Torani, San Leandro, CA, USA)) once a day from the time pregnancy was confirmed until delivery. The caloric value of the administration was made so as not to influence body weight or skew nutritional value of the diet among all treatment groups. Both interventions were applied only during gestation. Although most mothers were allowed to deliver naturally, cesarean delivery was performed for fetal indications when recommended by veterinarians (2 for each of the LC and OC groups, and 1 for the OP group). These mothers did not accept their infant following birth, so foster mothers were provided. Sample Collection and pre-processing prior to sample storage The animal caretakers and researchers who collected samples were blinded for group assignment by coding all animals by IDs. The collected biological samples were randomized by using random numbers and the group assignment was blinded during the data collection. Both mothers (during pregnancy) and infants were weighed every week. One day before sample collection, food was removed 30 min after the afternoon feeding, and biological samples were collected prior to the morning feeding. To collect biological samples, animals were anesthetized using 5–30 mg/kg ketamine or 5–8 mg/kg telazol. Both maternal and infant blood was collected using 5 mL lavender top (EDTA) tubes (Monoject, Cardinal Health, Dublin, OH, USA) and urine was collected from the bladder by ultrasound-guided transabdominal cystotomy using a 22-gauge needle and stored in a 15 mL Falcon tube. A placental sample was collected at GD150 transabdominally under ultrasound guidance using an 18-gauge needle attached to a sterile syringe. Sample processing was as previously described in (Hasegawa et al., 2022). Necropsy was conducted between 9:30 am–1:30 pm. First, infants at the age of PD180 were fasted and anesthetized with ketamine, and plasma and urine were collected. Then, euthanasia was performed with 120 mg/kg pentobarbital, followed by heparin injection, clamping of the descending aorta, and flushing with saline until clear. The kidney and brain (amygdala, hippocampus, hypothalamus, and prefrontal cortex) were collected, weighed, and immediately frozen on dry ice or liquid nitrogen to store at -80 °C until further analyses. Metabolite extraction and analysis by 1H NMR, and measurement of insulin, cholesterol, cytokine, and cortisol Detailed procedures were previously described (Hasegawa et al., 2022). Briefly, plasma and urine samples were filtered using Amicon Ultra Centrifugal Filter (3k molecular weight cutoff; Millipore, Billerica, MA, USA), and the supernatant was used for analysis. For both the placental and brain tissue samples, polar metabolites were extracted using our previously reported method (Hasegawa et al., 2020). A total of 180 μL of sample (tissue extract or filtered urine or serum) was transferred to 3 mm Bruker NMR tubes (Bruker, Billerica, MA, USA). Within 24 h of sample preparation, all 1H NMR spectra were acquired using the noesypr1d pulse sequence on a Bruker Avance 600 MHz NMR spectrometer (Bruker, Billerica, MA, USA) (O’Sullivan et al., 2013). Chenomx NMRSuite (version 8.1, Chenomx Inc., Edmonton, Canada) (Weljie et al., 2006) was used to identify and quantify metabolites. Heparin-treated plasma samples were used to measure insulin and 17 cytokines and chemokines (hs-CRP, Granulocyte-macrophage colony-stimulating factor, IFN-γ, TNF-α, transforming growth factor-α, monocyte chemoattractant protein-1, macrophage inflammatory protein-1β (MIP-1β), and interleukin (IL)-1β, IL-1 receptor antagonist (IL-1ra), IL-2, IL-6, IL-8, IL-10, IL-12/23 p40, IL-13, IL-15, and IL-17A) using a multiplex Bead-Based Kit (Millipore) on a Bio-Plex 100 (Bio-rad, Hercules, CA) following the manufacturer’s protocol. For each sample, a minimum of fifty beads per region were collected and analyzed with Bio-Plex Manager software using a 5-point standard curve with immune marker quantities extrapolated based on the standard curve. Two samples were removed for analysis of TNF-α and IL-1ra as technical errors (both from Animal ID 1132103: 895.2 and 1115.1 pg/mL at gestational days (GD) 90; 510.8 and 617.2 pg/mL at GD120, respectively). Plasma cholesterol level was measured by Clinical Laboratory Diagnostic Product (OSR6116) on Beckman Coulter AU480 (Beckman Coulter, Brea, CA). Infant plasma cortisol level at PD110 was assessed as previously described (Vandeleest et al., 2019; Walker et al., 2018). In short, infants were transferred to a test room at 9 am and blood was drawn at 11 am (Sample 1), followed by another blood collection at 4 pm (Sample 2) and intramuscular injection of 500 μg/kg dexamethasone (Dex) (American Regent Laboratories, Inc., Shirley, NY). On the next day, a blood sample was collected at 8:30 am (Sample 3), and then 2.5 IU of adrenocorticotropic hormone (Amphastar Pharmaceuticals, Inc., Rancho Cucamonga, CA) was injected intramuscularly. The last blood was collected (Sample 4) 30 min after adrenocorticotropic hormone injection. The collected blood samples were processed and stored, and cortisol concentration was assessed by a chemiluminescent assay on the ADVIA Centaur CP platform

Background: Standard pediatric growth curves cannot be used to impute missing height or weight measurements in individual children. The Michaelis-Menten equation, used for characterizing substrate-enzyme saturation curves, has been shown to model growth in many organisms including nonhuman vertebrates. We investigated whether this equation could be used to interpolate missing growth data in children in the first three years of life. Methods: We developed a modified Michaelis-Menten equation and compared expected to actual growth, first in a local birth cohort (N=97) then in a large, outpatient, pediatric sample (N=14,695). Results: The modified Michaelis-Menten equation showed excellent fit for both infant weight (median RMSE: boys: 0.22kg [IQR:0.19; 90%<0.43]; girls: 0.20kg [IQR:0.17; 90%<0.39]) and height (median RMSE: boys: 0.93cm [IQR:0.53; 90%<1.0]; girls: 0.91cm [IQR:0.50;90%<1.0]). Growth data were modeled accurately with as few as four values from routine well-baby ..., Sources of data: Information on infants was ascertained from two sources: the STORK birth cohort and the STARR research registry. (1) Detailed methods for the STORK birth cohort have been described previously. In brief, a multiethnic cohort of mothers and babies was followed from the second trimester of pregnancy to the babies’ third birthday. Healthy women aged 18–42 years with a single-fetus pregnancy were enrolled. Households were visited every four months until the baby’s third birthday (nine baby visits), with the weight of the baby at each visit recorded in pounds. Medical charts were abstracted for birth weight and length. (2) STARR (starr.stanford.edu) contains electronic medical record information from all pediatric and adult patients seen at Stanford Health Care (Stanford, CA). STARR staff provided anonymized information (weight, height and age in days for each visit through age three years; sex; race/ethnicity) for all babies during the period 03/2013–01/2022 followed from bi..., The R code, as written in RStudio, are saved as MME_weights.RMD, MME_heights.RMD, MME_predictions_weights.RMD, and MME_predictions_heights.RMD. The tab-delimited and anonymized source data for weights and heights (both jittered) are posted. These can be used with the R code-but the user will need to correct input and output filepaths used in the script. The HTML version of these files is available as well, in case viewing the scripts without opening them in R is desired. R_sessionInfo.txt contains the R software version, as well as the versions of the packages included in the code. See the methods section for the description of the starting parameters for the nls() function., # Data for: A modified Michaelis-Menten equation estimates growth from birth to 3 years in healthy babies in the US

https://doi.org/10.5061/dryad.4j0zpc8jf

Description of the data and file structure

Data for this study include, per baby: sex, age in days, and, over time, weight in Kg and height in cm. Each baby had at least 5 visits. Our goal was to fit each baby’s data to a curve as described by a modified Michaelis-Menten equation, allowing interpolation of missing weight or height values. Among the subset of all infants who had 7 well-baby visits in the first year of life, and 12 visits over 3 years, we further explored the minimum number of, and which, data points were necessary for good fit. Finally, among babies with 5 time points in year 1, and 2 in both year 2 and year 3, we examined whether weight or height data early in life could predict growth in later months.

To meet anonymization guidelines, we are providing only STARR dat...

1. Weighted estimates calculated using the examination weight; 95% confidence intervals.2. Diabetes was defined using self-reported diabetes.3. Chronic kidney disease was defined using self-reported disease or a glomerular filtration rate of 15–60 mL/min per 1.73 m2.4. Average number of drinks per day over the past year.5. Self-reported oral contraceptive use.6. Height and weight were measured during the examination.7. Hypertension was defined as an average systolic blood pressure ≥140 mmHg, average diastolic blood pressure ≥90 mmHg, or self-reported currently taking anti-hypertensives.

Baseline (mean, standard deviation [SD]) characteristics and average 4-y lifestyle changes (mean and 1st to 99th percentile range) of men and women in three prospective cohorts.

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Women Health App Market Size 2024-2028

The women health app market size is forecast to increase by USD 2.83 billion at a CAGR of 19.2% between 2023 and 2028.

The women's health app market is experiencing significant growth due to increasing awareness regarding the benefits of maintaining a healthy lifestyle. This trend is driving companies to develop innovative and user-friendly applications that cater to the unique health needs of women. However, compatibility issues with various operating systems pose a challenge for market expansion. To address this, companies are implementing strategic partnerships and collaborations to ensure their apps are compatible with multiple platforms. Additionally, integrating advanced features such as artificial intelligence and machine learning can enhance user experience and provide personalized health recommendations. Overall, the women's health app market is poised for growth, with companies focusing on addressing user needs, ensuring compatibility, and leveraging technology to provide effective and convenient solutions.

What will be the Size of the Women Health App Market During the Forecast Period?

Request Free SampleThe women's health app market is experiencing significant growth due to the increasing awareness of various health conditions affecting women and the adoption of digital health solutions. Hormonal disparities, osteoarthritis, anemia, obesity, menstrual cycles, depression, fibromyalgia, and menopause diseases are some of the common health concerns addressed by these apps. The aging population and the rise in women employment have fueled the demand for digital health solutions, including telemedicine, fertility monitoring, menstrual health, fitness and nutrition apps, and pregnancy care. Smart devices and health apps enable women to manage their weight, track their ovulation, monitor their menstrual cycles, and receive personalized fitness and nutrition plans.Medical devices integrated with digital technologies, such as pregnancy trackers and 5G-enabled devices, offer advanced features for disease management and maternity care. The prevalence of cancer and other chronic diseases among women further emphasizes the importance of digital health solutions. Women awareness programs and initiatives are also driving the market growth by promoting the benefits of digital technologies in managing various health conditions. Overall, the women's health app market is expected to continue its robust growth trajectory, offering innovative solutions to cater to the unique health needs of women.

How is this Women Health App Industry segmented and which is the largest segment?

The women health app industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. TypeMenstrual healthFitness and nutritionPregnancy trackingOthersGeographyNorth AmericaUSEuropeGermanyFranceAPACChinaIndiaSouth AmericaMiddle East and Africa

By Type Insights

The menstrual health segment is estimated to witness significant growth during the forecast period.

The women's health app market is experiencing significant growth, particularly In the area of menstrual health. These apps enable users to track menstrual cycles, predict periods, and monitor fertile windows. Some apps offer additional features, such as recording menstrual symptoms and sexual activity. These tools aid women in planning pregnancies and managing menstrual health. For instance, the Clue app provides options for tracking menstrual migraines, period-related acne, and other symptoms. The aging population, cultural factors, and increasing digital health solutions are driving the demand for these apps. Telemedicine platforms, smartphone usage, and health management apps are also contributing to the market's expansion.Chronic conditions, such as osteoarthritis, anemia, depression, fibromyalgia, and menopause diseases, are being addressed through digital tools. Health technology, including artificial intelligence (AI) and machine learning, is being integrated into personalized healthcare solutions. Wearable devices, virtual reality (VR), and digital startups are also playing a role in this sector. However, concerns regarding cybersecurity must be addressed to ensure user privacy. Health metrics tracking, fitness management, disease management, and pregnancy care are some of the key areas where women's health apps are making an impact. The market is expected to grow further with the advent of 5G technologies and the increasing prevalence of cancer and other health issues among women.

Get a glance at the Women Health App Industry report of share of various segments Request Free Sample

The Menstrual health segment was valued at USD 508.80 billion in 2018 and showed a gradual increase during the forecast period.

Regional

United States US: Prevalence of Stunting: Height for Age: % of Children Under 5, Modeled Estimate data was reported at 4.200 % in 2024. This records an increase from the previous number of 4.000 % for 2023. United States US: Prevalence of Stunting: Height for Age: % of Children Under 5, Modeled Estimate data is updated yearly, averaging 2.800 % from Dec 2000 (Median) to 2024, with 25 observations. The data reached an all-time high of 4.200 % in 2024 and a record low of 2.500 % in 2012. United States US: Prevalence of Stunting: Height for Age: % of Children Under 5, Modeled Estimate 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 stunting is the percentage of children under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0-59 months. For children up to two years old height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO's 2006 Child Growth Standards.;UNICEF, WHO, World Bank: Joint child Malnutrition Estimates (JME).;Weighted average;Undernourished children have lower resistance to infection and are more likely to die from common childhood ailments such as diarrheal diseases and respiratory infections. Frequent illness saps the nutritional status of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth (UNICEF). Being even mildly underweight increases the risk of death and inhibits cognitive development in children. And it perpetuates the problem across generations, as malnourished women are more likely to have low-birth-weight babies. Stunting, or being below median height for age, is often used as a proxy for multifaceted deprivation and as an indicator of long-term changes in malnutrition. Estimates are modeled estimates produced by the JME. Primary data sources of the anthropometric measurements are national surveys. These surveys are administered sporadically, resulting in sparse data for many countries. Furthermore, the trend of the indicators over time is usually not a straight line and varies by country. Tracking the current level and progress of indicators helps determine if countries are on track to meet certain thresholds, such as those indicated in the SDGs. Thus the JME developed statistical models and produced the modeled estimates.