Le package {inca3} est un package qui contient les jeux de données issus de l’étude inca3 de l’ANSES.
Il a pour objectif de faciliter l’utilisation de ces données pour le logiciel R.
Présentation des données
Les études INCA permettent de situer l’alimentation de la population au regard des recommandations du Programme National Nutrition Santé (PNNS) et d’envisager de poursuivre, modifier ou renforcer les priorités de la politique nutritionnelle en France.
Installation du package
Pour installer le package :
# install.packages("remotes")
remotes::install_github("thinkr-open/inca3", build_vignettes = FALSE)Utilisation
Description des individus suivis
head(description_indiv_decode)
#> # A tibble: 6 x 185
#> NOMEN NOIND ech enf_allaite pop1 pop2 pop3 pond_indiv_adu_…
#> <dbl> <dbl> <chr> <chr> <chr> <chr> <chr> <dbl>
#> 1 1.10e6 1.10e8 Adul… <NA> Oui Oui Oui 11415.
#> 2 1.10e6 1.10e8 Adul… <NA> Oui Oui Oui 4644.
#> 3 1.10e6 1.10e8 Adul… <NA> Oui Oui Oui 6017.
#> 4 1.10e6 1.10e8 Adul… <NA> Oui Oui Oui 1782.
#> 5 1.10e6 1.10e8 Adul… <NA> Oui Oui Oui 2359.
#> 6 1.10e6 1.10e8 Adul… <NA> Oui Oui Non 13624.
#> # … with 177 more variables: pond_indiv_enf_pop1 <dbl>,
#> # pond_indiv_adu_pop2 <dbl>, pond_indiv_enf_pop2 <dbl>,
#> # pond_indiv_adu_pop3 <dbl>, pond_indiv_enf_pop3 <dbl>, pond_men_pop1 <dbl>,
#> # pond_men_pop2 <dbl>, zae <chr>, strate <chr>, fpc1 <dbl>, fpc2 <dbl>,
#> # fpc3 <dbl>, saison_pop1 <chr>, saison_pop2 <chr>, saison_pop3 <chr>,
#> # region_adm_12cl <chr>, region_inca3 <chr>, agglo_5cl <chr>, sex_PS <chr>,
#> # tage_PS <chr>, tage_PS_mois <chr>, lien_rep_enf <chr>,
#> # diplome_interv <chr>, etude_4cl_interv <chr>, situ_prof_5cl_interv <chr>,
#> # atrav_interv <chr>, trav_nuit_interv <chr>, trav_nuit_2cl_interv <chr>,
#> # PCS_8cl_interv <chr>, PCS_4cl_interv <chr>, tps_travail_interv <chr>,
#> # vacances_interv <chr>, interv_PR <chr>, sex_PR <chr>, tage_PR <chr>,
#> # lien_interv_PR <chr>, lien_PS_PR <chr>, diplome_PR <chr>,
#> # etude_4cl_PR <chr>, atrav_PR <chr>, PCS_8cl_PR <chr>, PCS_4cl_PR <chr>,
#> # tps_travail_PR <chr>, stat_log_2cl <chr>, soins <chr>, situ_fin_3cl <chr>,
#> # revenu <chr>, RUC_4cl <chr>, nbpers <dbl>, nbadu <dbl>, nbenf <dbl>,
#> # situ_alim_statut <chr>, IA_statut <dbl>, IA_score <dbl>, taille_m <dbl>,
#> # taille_d <dbl>, taille <dbl>, poids_m <dbl>, poids_d <dbl>, poids <dbl>,
#> # imc <dbl>, statnut <chr>, maladie_allergie_alim <chr>,
#> # intoall_confirm_med <chr>, regime_vegetarien <chr>, regime_allergie <chr>,
#> # regime_maigrir_med <chr>, regime_maigrir_choix <chr>,
#> # regime_autre_med <chr>, regime_raisonmed_libelle <chr>,
#> # regime_poidsstable <chr>, regime_forme <chr>, regime_autreraison <chr>,
#> # regime_non <chr>, veget_viande <chr>, veget_prodmer <chr>,
#> # veget_prodlait <chr>, veget_oeuf <chr>, veget_miel <chr>,
#> # veget_autre_alim <chr>, veget_autre_alim_libelle <lgl>,
#> # allergie_laitvache <chr>, allergie_prepainfsoja <chr>,
#> # allergie_prepainfamande <chr>, allergie_gluten <chr>,
#> # allergie_farineble <chr>, allergie_lupin <chr>, allergie_arachide <chr>,
#> # allergie_fruitcoque <chr>, allergie_fruitcoque_libelle <chr>,
#> # allergie_oeuf <chr>, allergie_poisson <chr>, allergie_crustace <chr>,
#> # allergie_mollusque <chr>, allergie_soja <chr>, allergie_sesame <chr>,
#> # allergie_moutarde <chr>, allergie_sulfite <chr>, allergie_celeri <chr>,
#> # allergie_autres_fruitleg <chr>, …Composition des consommations alimentaires des individus
head(conso_compo_alim)
#> # A tibble: 6 x 109
#> POPULATION NOIND NUM_LIGNE R24_num R24_nombre R24_pond occ_hdeb occ_type
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <drtn> <dbl>
#> 1 Pop3 1.10e8 3 1 3 1 39600 s… 4
#> 2 Pop3 1.10e8 16 1 3 1 45000 s… 5
#> 3 Pop3 1.10e8 800001 1 3 1 45000 s… 5
#> 4 Pop3 1.10e8 6 1 3 1 45000 s… 5
#> 5 Pop3 1.10e8 14 1 3 1 45000 s… 5
#> 6 Pop3 1.10e8 7 1 3 1 45000 s… 5
#> # … with 101 more variables: occ_lieu <dbl>, occ_alim_libelle <chr>,
#> # occ_alim_num <dbl>, occ_alim_num_seq <dbl>, gpe_INCA3 <dbl>,
#> # aliment_code_INCA3 <dbl>, aliment_libelle_INCA3 <chr>,
#> # aliment_code_FX <chr>, aliment_libelle_FX <chr>, qte_conso <dbl>,
#> # qte_conso_pond <dbl>, facette_01 <chr>, facette_01_libelle <chr>,
#> # facette_02 <chr>, facette_02_libelle <chr>, facette_03 <chr>,
#> # facette_03_libelle <chr>, facette_04 <chr>, facette_04_libelle <chr>,
#> # facette_05 <chr>, facette_05_libelle <chr>, facette_06 <chr>,
#> # facette_06_libelle <chr>, facette_07 <chr>, facette_07_libelle <chr>,
#> # facette_08 <chr>, facette_08_libelle <chr>, facette_09 <chr>,
#> # facette_09_libelle <chr>, facette_10 <chr>, facette_10_libelle <chr>,
#> # facette_12 <chr>, facette_12_libelle <chr>, aliment_marque_bio <dbl>,
#> # aliment_marque_enrichi <dbl>, facette_13 <chr>, facette_13_libelle <chr>,
#> # facette_14 <chr>, facette_14_libelle <chr>, facette_19 <chr>,
#> # facette_19_libelle <chr>, facette_20 <chr>, facette_20_libelle <chr>,
#> # facette_25 <chr>, facette_25_libelle <chr>, facette_27 <chr>,
#> # facette_27_libelle <chr>, aet <dbl>, aesa <dbl>, proteines <dbl>,
#> # glucides <dbl>, sucres <dbl>, amidon <dbl>, polyols <dbl>, fibres <dbl>,
#> # acides_organiques <dbl>, lipides <dbl>, ags <dbl>, ag_16_0 <dbl>,
#> # ag_18_0 <dbl>, ag_14_0 <dbl>, ag_12_0 <dbl>, ag_10_0 <dbl>, ag_04_0 <dbl>,
#> # ag_06_0 <dbl>, ag_08_0 <dbl>, agmi <dbl>, ag_18_1_ole <dbl>, agpi <dbl>,
#> # ag_18_2_lino <dbl>, ag_18_3_a_lino <dbl>, ag_20_4_ara <dbl>,
#> # ag_20_5_epa <dbl>, ag_20_6_dha <dbl>, alcool <dbl>, eau <dbl>,
#> # retinol <dbl>, beta_carotene <dbl>, vitamine_b1 <dbl>, vitamine_b2 <dbl>,
#> # vitamine_b3 <dbl>, vitamine_b5 <dbl>, vitamine_b6 <dbl>, vitamine_b9 <dbl>,
#> # vitamine_b12 <dbl>, vitamine_c <dbl>, vitamine_d <dbl>, vitamine_e <dbl>,
#> # vitamine_k2 <dbl>, sodium <dbl>, sel <dbl>, magnesium <dbl>,
#> # phosphore <dbl>, potassium <dbl>, calcium <dbl>, manganese <dbl>,
#> # fer <dbl>, cuivre <dbl>, zinc <dbl>, selenium <dbl>, …Réferences
Carine Dubuisson, Ariane Dufour, Sandrine Carrillo, Peggy Drouillet-Pinard, Sabrina Havard, Jean-Luc Volatier (2019). The Third French Individual and National Food Consumption (INCA3) Survey 2014-2015: method, design and participation rate in the framework of a European harmonization process. Public Health Nutrition: 22(4), 584–600. doi:10.1017/S1368980018002896.
Comment ?