In financial year 2012, about ** percent of urban adults consumed the recommended amount of cereals in a day in northern India. However, only around ** percent of the urban people consumed the recommended amount of vegetables per day.

The Northern Indian state of Bihar had over ************* people per high court judge as of December 2022. By contrast, the eastern state of Sikkim had over ****** thousand people per judge that year.

Background: A heavy burden of cardiometabolic conditions on low- and middle-income countries like India that are rapidly undergoing urbanization remains unaddressed. Indians are known to have high levels of triglycerides and low levels of HDL-C along with moderately higher levels of LDL-C. The genome-wide findings from Western populations need to be validated in an Indian context for a better understanding of the underlying etiology of dyslipidemia in India.Objective: We aim to validate 12 genetic variants associated with lipid levels among rural and urban Indian populations and derive unweighted and weighted genetic risk scores (uGRS and wGRS) for lipid levels among the Indian population.Methods: Assuming an additive model of inheritance, linear regression models adjusted for all the possible covariates were run to examine the association between 12 genetic variants and total cholesterol, triglycerides, HDL-C, LDL-C, and VLDL-C among 2,117 rural and urban Indian participants. The combined effect of validated loci was estimated by allelic risk scores, unweighted and weighted by their effect sizes.Results: The wGRS for triglycerides and VLDL-C was derived based on five associated variants (rs174546 at FADS1, rs17482753 at LPL, rs2293889 at TRPS1, rs4148005 at ABCA8, and rs4420638 at APOC1), which was associated with 36.31 mg/dL of elevated triglyceride and VLDL-C levels (β = 0.95, SE = 0.16, p < 0.001). Similarly, every unit of combined risk score (rs2293889 at TRPS1 and rs4147536 at ADH1B) was associated with 40.62 mg/dL of higher total cholesterol (β = 1.01, SE = 0.23, p < 0.001) and 33.97 mg/dL of higher LDL-C (β = 1.03, SE = 0.19, p < 0.001) based on its wGRS (rs2293889 at TRPS1, rs4147536 at ADH1B, rs4420638 at APOC1, and rs660240 at CELSR2). The wGRS derived from five associated variants (rs174546 at FADS1, rs17482753 at LPL, rs4148005 at ABCA8, rs4420638 at APOC1, and rs7832643 at PLEC) was associated with 10.64 mg/dL of lower HDL-C (β = −0.87, SE = 0.14, p < 0.001).Conclusion: We confirm the role of eight genome-wide association study (GWAS) loci related to different lipid levels in the Indian population and demonstrate the combined effect of variants for lipid traits among Indians by deriving the polygenic risk scores. Similar studies among different populations are required to validate the GWAS loci and effect modification of these loci by lifestyle and environmental factors related to urbanization.

The Kashmiri population is an ethno-linguistic group that resides in the Kashmir Valley in northern India. A longstanding hypothesis is that this population derives ancestry from Jewish and/or Greek sources. There is historical and archaeological evidence of ancient Greek presence in India and Kashmir. Further, some historical accounts suggest ancient Hebrew ancestry as well. To date, it has not been determined whether signatures of Greek or Jewish admixture can be detected in the Kashmiri population. Using genome-wide genotyping and admixture detection methods, we determined there are no significant or substantial signs of Greek or Jewish admixture in modern-day Kashmiris. The ancestry of Kashmiri Tibetans was also determined, which showed signs of admixture with populations from northern India and west Eurasia. These results contribute to our understanding of the existing population structure in northern India and its surrounding geographical areas.

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Population Health Management Market Size 2025-2029

The population health management market size is valued to increase USD 19.40 billion, at a CAGR of 10.7% from 2024 to 2029. Rising adoption of healthcare IT will drive the population health management market.

Major Market Trends & Insights

North America dominated the market and accounted for a 68% growth during the forecast period.
By Component - Software segment was valued at USD 16.04 billion in 2023
By End-user - Large enterprises segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 113.32 billion
Market Future Opportunities: USD 19.40 billion
CAGR : 10.7%
North America: Largest market in 2023

Market Summary

The market encompasses a continually evolving landscape of core technologies and applications, service types, and regulatory frameworks. With the rising adoption of healthcare IT solutions, population health management platforms are increasingly being adopted to improve patient outcomes and reduce costs. According to a recent study, The market is expected to witness a significant growth, with over 30% of healthcare organizations implementing these solutions by 2025. The focus on personalized medicine and the need to manage the rising cost of healthcare are major drivers for this trend. Core technologies such as data analytics, machine learning, and telehealth are transforming the way healthcare providers manage patient populations.
Despite these opportunities, challenges such as data privacy concerns, interoperability issues, and the high cost of implementation persist. The market is further shaped by regional differences in regulatory frameworks and healthcare infrastructure. For instance, in North America, the Affordable Care Act has fueled the adoption of population health management solutions, while in Europe, the European Medicines Agency's focus on personalized medicine is driving demand.

What will be the Size of the Population Health Management Market during the forecast period?

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How is the Population Health Management Market Segmented and what are the key trends of market segmentation?

The population health management industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Component

  Software
  Services


End-user

  Large enterprises
  SMEs


Delivery Mode

  On-Premise
  Cloud-Based
  Web-Based
  On-Premise
  Cloud-Based


End-Use

  Providers
  Payers
  Employer Groups
  Government Bodies
  Providers
  Payers
  Employer Groups


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Component Insights

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

The market is experiencing significant growth, with the software segment playing a crucial role in this expansion. Currently, remote patient monitoring solutions are witnessing a 25% adoption rate, enabling healthcare providers to monitor patients' health in real-time and intervene promptly when necessary. Additionally, predictive modeling and risk stratification models are being utilized to identify high-risk patients and provide personalized care plans, contributing to a 21% increase in disease management efficiency. Furthermore, the integration of electronic health records, wellness programs, care coordination platforms, and value-based care models is fostering a data-driven approach to healthcare, leading to a 19% reduction in healthcare costs.

Health equity initiatives and healthcare data analytics are essential components of population health management, ensuring equitable access to care and improving healthcare quality metrics. Looking ahead, the market is expected to grow further, with utilization management and care management programs seeing a 27% increase in implementation. Preventive health programs and clinical decision support systems are also anticipated to experience a 24% surge in adoption, emphasizing the importance of proactive care and early intervention. Moreover, population health strategies are evolving to incorporate behavioral health integration, interoperability standards, and disease registry data to provide comprehensive care. The use of disease prevalence data and public health surveillance is becoming increasingly crucial in addressing population health challenges and improving overall health outcomes.

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The Software segment was valued at USD 16.04 billion in 2019 and showed a gradual increase during the forecast period.

In conclusion, the market is

The Country-Level Population and Downscaled Projections Based on Special Report on Emissions Scenarios (SRES) B2 Scenario, 1990-2100, were based on the UN 1998 Medium Long Range Projection for the years 1995 to 2100. The official version projects population for 8 regions of the world including Africa, Asia (minus India and China), India, China, Europe, Latin America, Northern America, and Oceania. This data set is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

The population density of the northern state of Uttar Pradesh in India recorded *** people for every square kilometer in 2011, the latest available census. This was a doubling compared to the value in 1981.

BackgroundÂ

Large carnivores maintain the stability and functioning of ecosystems. Currently, many carnivore species face declining population sizes due to natural and anthropogenic pressures. The leopard, Panthera pardus, is probably the most widely distributed and highly adaptable large felid globally, still persisting in most of its historic range. However, we lack subspecies-level data on country or regional scale on population trends, as ecological monitoring approaches are difficult to apply on such wide-ranging species. We used genetic data from leopards sampled across the Indian subcontinent to investigate population structure and patterns of demographic decline.Â

MethodsÂ

We collected faecal samples from the Terai-Arc landscape of north India and identified 56 unique individuals using a panel of 13 microsatellite markers. We merged this data with already available 143 leopard individuals and assessed genetic structure at country scale. Subsequently, we investigated the...

BackgroundHeadache disorders now represent a major public health problem globally. It is more prevalent in developing countries with the rising trends of headache disorders observed in young adults affecting their quality of life negatively. Very little information is available on the epidemiology of headache disorders in the Jammu Division of the north Indian population.AimThe aim of the present study was to find out the prevalence of headache and its two major types, i.e., migraine and tension-type headache (TTH), in the population of the Jammu Division.MethodsThe present study was conducted in two phases: (Phase I: face-to-face interview and Phase II: E-based sampling) and the sufferers of headaches were incorporated into the study based on the International Classification of Headache Disorder-3 (ICHD-3) criteria for a representative sample. Frequency distribution and mean ± standard deviation were used in descriptive statistics to describe the data sets, while a t-test, chi-square test, multiple logistic regression, and prevalence ratio were used in inferential statistics.ResultsIn the present study, a total of 3,148 patients were recruited, with an overall prevalence of headache of 53.84%, with a majority of females (38.18%) over males (15.66%). As regards the type of headache, migraine was found to be of the more prevalent (33.25%) type than the TTH (20.58%). Females suffering from migraine showed the highest prevalence (25.28%), in contrast to females suffering from the TTH (12.89%). Sociodemographic variables, such as gender [female; AOR = 2.46, 95% CI (2.12–2.85), p-value < 0.0001] and marital status [married; AOR: 1.46, 95% CI (1.11–1.92) p-value = 0.006], showed a significant association with the headache.ConclusionThe present study shows that the prevalence of headache is high in the Jammu Division of Jammu and Kashmir (J&K) India, with migraine being the highly prevalent type.

In Ayurveda system of medicine individuals are classified into seven constitution types, “Prakriti”, for assessing disease susceptibility and drug responsiveness. Prakriti evaluation involves clinical examination including questions about physiological and behavioural traits. A need was felt to develop models for accurately predicting Prakriti classes that have been shown to exhibit molecular differences. The present study was carried out on data of phenotypic attributes in 147 healthy individuals of three extreme Prakriti types, from a genetically homogeneous population of Western India. Unsupervised and supervised machine learning approaches were used to infer inherent structure of the data, and for feature selection and building classification models for Prakriti respectively. These models were validated in a North Indian population. Unsupervised clustering led to emergence of three natural clusters corresponding to three extreme Prakriti classes. The supervised modelling approaches could classify individuals, with distinct Prakriti types, in the training and validation sets. This study is the first to demonstrate that Prakriti types are distinct verifiable clusters within a multidimensional space of multiple interrelated phenotypic traits. It also provides a computational framework for predicting Prakriti classes from phenotypic attributes. This approach may be useful in precision medicine for stratification of endophenotypes in healthy and diseased populations.

Census: Population: Assam: North Lakhimpur data was reported at 59,814.000 Person in 03-01-2011. This records an increase from the previous number of 54,285.000 Person for 03-01-2001. Census: Population: Assam: North Lakhimpur data is updated decadal, averaging 6,576.000 Person from Mar 1921 (Median) to 03-01-2011, with 9 observations. The data reached an all-time high of 59,814.000 Person in 03-01-2011 and a record low of 1,966.000 Person in 03-01-1921. Census: Population: Assam: North Lakhimpur data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAC004: Census: Population: By Towns and Urban Agglomerations: Assam.

Census: Population: Goa: Goa Velha (North) data was reported at 4,322.000 Person in 03-01-2011. This records a decrease from the previous number of 5,395.000 Person for 03-01-2001. Census: Population: Goa: Goa Velha (North) data is updated decadal, averaging 4,858.500 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 5,395.000 Person in 03-01-2001 and a record low of 4,322.000 Person in 03-01-2011. Census: Population: Goa: Goa Velha (North) data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAC010: Census: Population: By Towns and Urban Agglomerations: Goa.

The following data set is information obtained about counties in the United States from 2010 through 2019 through the United States Census Bureau. Information described in the data includes the age distributions, the education levels, employment statistics, ethnicity percents, houseold information, income, and other miscellneous statistics. (Values are denoted as -1, if the data is not available)

Data Dictionary

The Country-Level Population and Downscaled Projections Based on Special Report on Emissions Scenarios (SRES) B2 Scenario, 1990-2100, were based on the UN 1998 Medium Long Range Projection for the years 1995 to 2100. The official version projects population for 8 regions of the world including Africa, Asia (minus India and China), India, China, Europe, Latin America, Northern America, and Oceania. This data set is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

Census: Population: Goa: Goa Velha (North): Male data was reported at 2,129.000 Person in 03-01-2011. This records a decrease from the previous number of 2,868.000 Person for 03-01-2001. Census: Population: Goa: Goa Velha (North): Male data is updated decadal, averaging 2,498.500 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 2,868.000 Person in 03-01-2001 and a record low of 2,129.000 Person in 03-01-2011. Census: Population: Goa: Goa Velha (North): Male data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAC010: Census: Population: By Towns and Urban Agglomerations: Goa.

Census: Population: Goa: Goa Velha (North): Female data was reported at 2,193.000 Person in 03-01-2011. This records a decrease from the previous number of 2,527.000 Person for 03-01-2001. Census: Population: Goa: Goa Velha (North): Female data is updated decadal, averaging 2,360.000 Person from Mar 2001 (Median) to 03-01-2011, with 2 observations. The data reached an all-time high of 2,527.000 Person in 03-01-2001 and a record low of 2,193.000 Person in 03-01-2011. Census: Population: Goa: Goa Velha (North): Female data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAC010: Census: Population: By Towns and Urban Agglomerations: Goa.

Comprehensive population and demographic data for Kattagaram (North) Village

The dataset contains details of tiger population estimation pertaining to tiger landscapes in the country

Note: 1. States have been categorised as Shivalik-Gangetic Plain Landscape Complex, Uttarakhand, Uttar Pradesh, Bihar. Shivalik-Gangetic includes: Central India Landscape Complex, Andhra Pradesh (Including Telangana), Chhattisgarh, Madhya Pradesh, Maharashtra, Odisha, Rajasthan, Jharkhand, Central Indian, Western Ghats Landscape Complex, Karnataka, Kerala, Tamil Nadu, Goa. Western Ghats includes: North East Hills and Brahmaputra Flood Plains, Assam, Arunachal Pradesh, Mizoram, Northern West Bengal, North East Hills and Brahmaputra includes Sundarbans. NB: Ranipur (Uttar Pradesh) is added in Shivalik landscape for convenience.

1. State population estimate does not add up to the landscape estimate due to common tigers, tiger outside protected areas, and model range limits.

Census: Population: Assam: North Lakhimpur: Male data was reported at 30,847.000 Person in 03-01-2011. This records an increase from the previous number of 28,912.000 Person for 03-01-2001. Census: Population: Assam: North Lakhimpur: Male data is updated decadal, averaging 4,327.000 Person from Mar 1921 (Median) to 03-01-2011, with 9 observations. The data reached an all-time high of 30,847.000 Person in 03-01-2011 and a record low of 1,204.000 Person in 03-01-1921. Census: Population: Assam: North Lakhimpur: Male data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAC004: Census: Population: By Towns and Urban Agglomerations: Assam.

Model A: compares variation between geographic regions (northern India, central India, and southern India), among populations within regions and within populations. Model B: compares variation between hosts (cotton, pigeonpea and chickpea), among populations within hosts and within populations. Model C: compares genetic variations between cropping seasons (season 2004–05, season 2005–06, season 2006–07), among populations within cropping seasons and within populations.