Chile CL: Population: Male: Ages 30-34: % of Male Population data was reported at 8.537 % in 2023. This records an increase from the previous number of 8.513 % for 2022. Chile CL: Population: Male: Ages 30-34: % of Male Population data is updated yearly, averaging 7.671 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 8.537 % in 2023 and a record low of 6.396 % in 1972. Chile CL: Population: Male: Ages 30-34: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Population and Urbanization Statistics. Male population between the ages 30 to 34 as a percentage of the total male population.;United Nations Population Division. World Population Prospects: 2024 Revision.;;

Actual value and historical data chart for Chile Population Ages 30 34 Female Percent Of Female Population

In Chile during 2024, there were ******* childbirths. In almost ** percent of them, the mother was between 30 and 34 years of age. The age group containing mothers between 25 and 29 years accounted for another **** percent of the total births.

Chile Population: Age: 30 to 34 data was reported at 1,100.606 Person th in Apr 2019. This records an increase from the previous number of 1,082.462 Person th for Mar 2019. Chile Population: Age: 30 to 34 data is updated monthly, averaging 1,029.063 Person th from Mar 2010 (Median) to Apr 2019, with 110 observations. The data reached an all-time high of 1,100.606 Person th in Apr 2019 and a record low of 984.364 Person th in Mar 2010. Chile Population: Age: 30 to 34 data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Chile – Table CL.G003: Population: by Age.

Actual value and historical data chart for Chile Population Ages 30 34 Male Percent Of Male Population

Chile Employment: Age 30 to 34 data was reported at 847.439 Person th in Apr 2019. This records an increase from the previous number of 830.775 Person th for Mar 2019. Chile Employment: Age 30 to 34 data is updated monthly, averaging 782.779 Person th from Mar 2010 (Median) to Apr 2019, with 110 observations. The data reached an all-time high of 847.439 Person th in Apr 2019 and a record low of 714.712 Person th in Mar 2010. Chile Employment: Age 30 to 34 data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Chile – Table CL.G014: Employment: NENE.

Chile CL: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 14.800 NA in 2016. This records a decrease from the previous number of 15.000 NA for 2015. Chile CL: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 16.000 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 17.600 NA in 2000 and a record low of 14.800 NA in 2016. Chile CL: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Actual value and historical data chart for Chile Mortality From Cvd Cancer Diabetes Or Crd Between Exact Ages 30 And 70 Percent

Chile CL: Population: Female: Ages 30-34: % of Female Population data was reported at 8.236 % in 2023. This records an increase from the previous number of 8.206 % for 2022. Chile CL: Population: Female: Ages 30-34: % of Female Population data is updated yearly, averaging 7.477 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 8.236 % in 2023 and a record low of 6.184 % in 1972. Chile CL: Population: Female: Ages 30-34: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Population and Urbanization Statistics. Female population between the ages 30 to 34 as a percentage of the total female population.;United Nations Population Division. World Population Prospects: 2024 Revision.;;

This report provides state-specific data from fiscal year 2001 about children's ages at the time of a public agency adoption finalization. Metadata-only record linking to the original dataset. Open original dataset below.

Chile CL: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data was reported at 10.100 NA in 2016. This records a decrease from the previous number of 10.200 NA for 2015. Chile CL: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data is updated yearly, averaging 10.900 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 12.000 NA in 2000 and a record low of 10.100 NA in 2016. Chile CL: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

This dataset accompanies planned publication 'Lava-ice interactions at late Pleistocene trachyte-basaltic andesite fissure eruptions, Quetrupillán Volcanic Complex (39°30′ S, 71°43′ W), southern Chile', as well as planned future publications on this volcanic complex. The Ar/Ar data and the Pb, Sr, and Nd data are for basalt and trachyte lava flows at Quetrupillán volcano. The Ar geochronology and isotope geochemistry will aid in the understanding of the timing of eruptive activity and glacial damming of lava flows, and magma source compositions studied in the planned publications. Samples were collected from Quetrupillán volcano by Dave McGarvie (Univ. of Lancaster, UK) and Isla Simmons (Univ. of Edinburgh, UK), who sent them to the USGS Denver for analysis. The analyses were performed from March 2021 to Feb 2023.

Sweden - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly was 72.70% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Sweden - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly - last updated from the EUROSTAT on November of 2025. Historically, Sweden - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly reached a record high of 76.00% in December of 2014 and a record low of 65.00% in December of 2010.

Chile CL: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 9.400 % in 2021. This records a decrease from the previous number of 9.900 % for 2020. Chile CL: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 12.700 % from Dec 2000 (Median) to 2021, with 22 observations. The data reached an all-time high of 14.400 % in 2001 and a record low of 9.400 % in 2021. Chile CL: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Social: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;Weighted average;This is the Sustainable Development Goal indicator 3.4.1 [https://unstats.un.org/sdgs/metadata/].

Croatia - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly was 61.50% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Croatia - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly - last updated from the EUROSTAT on November of 2025. Historically, Croatia - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly reached a record high of 61.50% in December of 2024 and a record low of 31.00% in December of 2012.

The food Retail market in Chile is dominated by the large presence of international players such as Cencosud and Walmart. In Confectionery market distribution, Hypermarkets & Supermarkets is the leading retail channel with 40.2% market share, followed by Convenience Stores with a 28.7% channel share There is a growing demand for exclusive and premium Chocolates in urban areas due to the rising incomes of Chileans Chilean children and adults face obesity issues and efforts are being taken by the Chilean authorities to govern policies regarding food ingredients. Chileans increasingly prefer better for you alternatives and innovative products due to increasing health concerns Indulgence and Changing Age Structure are the major consumer trends in Confectionery market in Chile The majority of the Chilean population is below 30 years of age and this has led to the growth of innovative Confectionery products with unique ingredients Read More

ABSTRACT Objective: To verify the presence of depression, age, level of schooling, occupation, marital status, number of children and nutritional status (maternal and of the child) in mothers of overweight and eutrophic children and relate the data to mother/child bonding. Methods: A total of 120 mothers of children aged up to 10 years participated; 30 of them were overweight and 30 were eutrophic (low-income bracket); 30 were overweight and 30 eutrophic (high-income bracket). The control group was composed of eutrophic children paired according to sex, age, level of schooling, and social condition. Data collection was made through interviews. The assessment instruments were: Mother/Child Bonding Assessment Protocol and Beck Depression Inventory. The nutritional classification was defined by calculation of the body mass index, as per the curves of the World Health Organization. For statistics, McNemar, χ2, and Fisher's exact tests were used. A 5% level of rejection of the null hypothesis was set. Results: There was no significant result between mother/child bonding and the variables studied, or between the presence of depression and level of schooling, marital status, occupation, and maternal nutritional status. Nevertheless, mothers of eutrophic children (high-income bracket) showed less depression than mothers of eutrophic children (low-income bracket). Mothers with three or more children displayed more depression than mothers with less than three children. Mothers under 30 years of age showed more depression than mothers aged 30 years or older. Conclusion: There was no significant result between mother/child bonding and the variables studied, but the bond was compromised in all mothers of the sample. There was a significant result regarding the presence of depression.

Poland - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly was 60.80% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Poland - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly - last updated from the EUROSTAT on November of 2025. Historically, Poland - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly reached a record high of 60.80% in December of 2024 and a record low of 31.00% in December of 2009.

Life table data for "Bounce backs amid continued losses: Life expectancy changes since COVID-19"

cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

These are CSV files of life tables over the years 2015 through 2021 across 29 countries analyzed in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

40-lifetables.csv

Life table statistics 2015 through 2021 by sex and region with uncertainty quantiles based on Poisson replication of death counts.

30-lt_input.csv

Life table input data.

• `id`: unique row identifier
• `region_iso`: iso3166-2 region codes
• `sex`: Male, Female, Total
• `year`: iso year
• `age_start`: start of age group
• `age_width`: width of age group, Inf for age_start 100, otherwise 1
• `nweeks_year`: number of weeks in that year, 52 or 53
• `death_total`: number of deaths by any cause
• `population_py`: person-years of exposure (adjusted for leap-weeks and missing weeks in input data on all cause deaths)
• `death_total_nweeksmiss`: number of weeks in the raw input data with at least one missing death count for this region-sex-year stratum. missings are counted when the week is implicitly missing from the input data or if any NAs are encounted in this week or if age groups are implicitly missing for this week in the input data (e.g. 40-45, 50-55)
• `death_total_minnageraw`: the minimum number of age-groups in the raw input data within this region-sex-year stratum
• `death_total_maxnageraw`: the maximum number of age-groups in the raw input data within this region-sex-year stratum
• `death_total_minopenageraw`: the minimum age at the start of the open age group in the raw input data within this region-sex-year stratum
• `death_total_maxopenageraw`: the maximum age at the start of the open age group in the raw input data within this region-sex-year stratum
• `death_total_source`: source of the all-cause death data
• `population_midyear`: midyear population (July 1st)
• `population_source`: source of the population count/exposure data
• `death_covid`: number of deaths due to covid
• `death_covid_date`: number of deaths due to covid as of
• `death_covid_nageraw`: the number of age groups in the covid input data
• `ex_wpp_estimate`: life expectancy estimates from the World Population prospects for a five year period, merged at the midpoint year
• `ex_hmd_estimate`: life expectancy estimates from the Human Mortality Database
• `nmx_hmd_estimate`: death rate estimates from the Human Mortality Database
• `nmx_cntfc`: Lee-Carter death rate projections based on trend in the years 2015 through 2019

Deaths

• source:
  • STMF input data series (https://www.mortality.org/Public/STMF/Outputs/stmf.csv)
  • ONS for GB-EAW pre 2020
  • CDC for US pre 2020
• STMF:
  • harmonized to single ages via pclm
  • pclm iterates over country, sex, year, and within-year age grouping pattern and converts irregular age groupings, which may vary by country, year and week into a regular age grouping of 0:110
  • smoothing parameters estimated via BIC grid search seperately for every pclm iteration
  • last age group set to [110,111)
  • ages 100:110+ are then summed into 100+ to be consistent with mid-year population information
  • deaths in unknown weeks are considered; deaths in unknown ages are not considered
• ONS:
  • data already in single ages
  • ages 100:105+ are summed into 100+ to be consistent with mid-year population information
  • PCLM smoothing applied to for consistency reasons
• CDC:
  • The CDC data comes in single ages 0:100 for the US. For 2020 we only have the STMF data in a much coarser age grouping, i.e. (0, 1, 5, 15, 25, 35, 45, 55, 65, 75, 85+). In order to calculate life-tables in a manner consistent with 2020, we summarise the pre 2020 US death counts into the 2020 age grouping and then apply the pclm ungrouping into single year ages, mirroring the approach to the 2020 data

Population

• source:
  • for years 2000 to 2019: World Population Prospects 2019 single year-age population estimates 1950-2019
  • for year 2020: World Population Prospects 2019 single year-age population projections 2020-2100
• mid-year population
  • mid-year population translated into exposures:
    • if a region reports annual deaths using the Gregorian calendar definition of a year (365 or 366 days long) set exposures equal to mid year population estimates
    • if a region reports annual deaths using the iso-week-year definition of a year (364 or 371 days long), and if there is a leap-week in that year, set exposures equal to 371/364\*mid_year_population to account for the longer reporting period. in years without leap-weeks set exposures equal to mid year population estimates. further multiply by fraction of observed weeks on all weeks in a year.

COVID deaths

• source: COVerAGE-DB (https://osf.io/mpwjq/)
• the data base reports cumulative numbers of COVID deaths over days of a year, we extract the most up to date yearly total

External life expectancy estimates

• source:
  • World Population Prospects (https://population.un.org/wpp/Download/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2019_Life_Table_Medium.csv), estimates for the five year period 2015-2019
  • Human Mortality Database (https://mortality.org/), single year and age tables

Slovenia - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly was 89.50% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Slovenia - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly - last updated from the EUROSTAT on November of 2025. Historically, Slovenia - Formal child care: Between 3 years and compulsory school age - childcare 30 hours or more weekly reached a record high of 89.60% in December of 2020 and a record low of 72.10% in December of 2021.