In 2023, the annual population growth in India was 0.88 percent. Between 1961 and 2023, the figure dropped by 1.52 percentage points, though the decline followed an uneven course rather than a steady trajectory.

About this dataset

Context

The dataset tabulates the Indian Shores population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Indian Shores across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Indian Shores was 1,192, a 0.50% decrease year-by-year from 2022. Previously, in 2022, Indian Shores population was 1,198, a decline of 0.17% compared to a population of 1,200 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Indian Shores decreased by 511. In this period, the peak population was 1,777 in the year 2004. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Indian Shores is shown in this column.
• Year on Year Change: This column displays the change in Indian Shores population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

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This dataset is a part of the main dataset for Indian Shores Population by Year. You can refer the same here

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Key words: Multi-morbidity, cross-sectional, household, active measurement, rural, India, pattern

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Why project population?
Population projections for a country are becoming increasingly important now than ever before. They are used primarily by government policy makers and planners to better understand and gauge future demand for basic services that predominantly include water, food and energy. In addition, they also support in indicating major movements that may affect economic development and in turn, employment and labour productivity. Consequently, this leads to amending policies in order to better adapt to the needs of society and to various circumstances.

Demographic projections and health interventions Demographic figures serve the foremost purpose of improving health and health related services among the population. Some of the government interventions include antenatal and neonatal care with the aim of reducing maternal and neonatal mortality and morbidity rates. In addition, it also focuses on improving immunization coverage across the country. Further, demographic estimates help in better preempting the needs of growing populations, such as the geriatric population within a country.

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Abstract

Vadu Rural Health Program, KEM Hospital Research Centre Pune has a rich tradition in health care and development being in the forefront of needs-based, issue-driven research over almost 35 years. During the decades of 1980 and 1990 the research at Vadu focused on mother and child with epidemiological and social science research exploring low birth weight, child survival, maternal mortality, safe abortion and domestic violence. The research portfolio has ever since expanded to include adult health and aging, non-communicable and communicable diseases and to clinical trials in recent years. It started with establishment of Health and Demographic Surveillance System at Vadu (HDSS Vadu) in August, 2002 that seeks to establish a quasi-experimental design setting to allow evaluation of impact of health interventions as well as monitor secular trends in diseases, risk factors and health behavior of humans.

The term "demographic surveillance" means to keep close track of the population dynamics. Vadu HDSS deals with keeping track of health issues and demographic changes in Vadu rural health program (VRHP) area. It is one of the most promising projects of national relevance that aims at establishing a quasi-experimental intervention research setting with the following objectives: 1) To create a longitudinal data base for efficient service delivery, future research, and linking all past micro-studies in Vadu area 2) Monitoring trends in public health problems 3) Keeping track of population dynamics 4) Evaluating intervention services

This dataset contains the events of all individuals ever resident during the study period (1 Jan. 2009 to 31 Dec. 2015).

Geographic coverage

Vadu HDSS falls in two administrative blocks: (1) Shirur and (2) Haweli of Pune district in Maharashtra in western India. It covers an area of approximately 232 square kilometers.

Analysis unit

Individual

Universe

Vadu HDSS covers as many as 50,000 households having 140,000 population spread across 22 villages.

Kind of data

Event history data

Frequency of data collection

Two rounds per year

Sampling procedure

Vadu area including 22 villages in two administrative blocks is the study area. This area was selected as this is primarily coverage area of Vadu Rural Health Program which is in function since more than four decade. Every individual household is included in HDSS. There is no sampling strategy employed as 100% population coverage in the area is expected.

Mode of data collection

Proxy Respondent [proxy]

Research instrument

Language of communication is in Marath or Hindi. The form labels are multilingual - in English and Marathi, but the data entered through the forms are in English only.

The following forms were used: - Field Worker Checklist Form - The checklist provides a guideline to ensure that all the households are covered during the round and the events occurred in each household are captured. - Enumeration Form: To capture the population details at the start of the HDSS or any addition of villages afterwards. - Pregnancy Form: To capture pregnancy details of women in the age group 15 to 49. - Birth Form: To capture the details of the birth events.
- Inmigration Form: To capture inward population movement from outside the HDSS area and also for movement within the HDSS area. - Outmigration Form: To capture outward population movement from inside the HDSS area and also for movement within the HDSS area. - Death Form: To capture death events.

Cleaning operations

Entered data undergo a data cleaning process. During the cleaning process all error data are either corrected in consultaiton with the data QC team or the respective forms are sent back to the field for re collection of correct data. Data editors have the access to the raw dataset for making necessary editing after corrected data are bought from the field.

For all individuals whose enumeration (ENU), Inmigration (IMG) or Birth (BTH) have occurred before the left censoring date (2009-01-01) and have not outmigrated (OMG) or not died (DTH) before the left censoring date (2009-01-01) are included in the dataset as Enumeration (ENU) with EventDate as the left censored date (2009-01-01). But the actual date of observation of the event (ENU, BTH, IMG) is retained in the dataset as observation date for these left censored ENU events. The individual is dropped from the dataset if their end event (OMG or DTH) is prior to the left censoring date (2009-01-01)

Response rate

On an average the response rate is 99.99% in all rounds over the years.

Sampling error estimates

Not Applicable

Data appraisal

Data is cleaned to an acceptable level against the standard data rules using Pentaho Data Integration Comminity Edition (PDI CE) tool. After the cleaning process, quality metrics were as follows:

CentreId MetricTable QMetric Illegal Legal Total Metric RunDate IN021 MicroDataCleaned Starts 1 301112 301113 0. 2017-05-31 20:06
IN021 MicroDataCleaned Transitions 0 667010 667010 0. 2017-05-31 20:07
IN021 MicroDataCleaned Ends 301113 2017-05-31 20:07
IN021 MicroDataCleaned SexValues 29 666981 667010 0. 2017-05-31 20:07
IN021 MicroDataCleaned DoBValues 575 666435 667010 0. 2017-05-31 20:07

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