Create older people indicators dataset from survey data collected using the standard RAM-OP questionnaire.

The indicator sets covered by the standard RAM-OP survey are:

Demographic indicators
Dietary intake indicators
Household hunger scale
Katz Index of Independence in Activities of Daily Living score
K6 Short form psychological distress score
Brief Community Screening Instrument for Dementia (CSID)
Health and health-seeking indicators
Income and income sources
Water, sanitation and hygiene (WASH) indicators
Anthropometry and screening
Visual impairment by "Tumbling E" method
Miscellaneous indicators
Washington Group on Disability

Usage

create_op(
  svy,
  indicators = c("demo", "food", "hunger", "disability", "adl", "mental", "dementia",
    "health", "income", "wash", "anthro", "oedema", "screening", "visual", "misc"),
  sex = c("mf", "m", "f")
)

create_op_demo(svy, sex = c("mf", "m", "f"))

create_op_food(svy, sex = c("mf", "m", "f"))

create_op_hunger(svy, sex = c("mf", "m", "f"))

create_op_adl(svy, sex = c("mf", "m", "f"))

create_op_disability(svy, sex = c("mf", "m", "f"))

create_op_mental(svy, sex = c("mf", "m", "f"))

create_op_dementia(svy, sex = c("mf", "m", "f"))

create_op_health(svy, sex = c("mf", "m", "f"))

create_op_income(svy, sex = c("mf", "m", "f"))

create_op_wash(svy, sex = c("mf", "m", "f"))

create_op_anthro(svy, sex = c("mf", "m", "f"))

create_op_oedema(svy, sex = c("mf", "m", "f"))

create_op_screening(svy, sex = c("mf", "m", "f"))

create_op_visual(svy, sex = c("mf", "m", "f"))

create_op_misc(svy, sex = c("mf", "m", "f"))

Arguments

svy: A data.frame() collected using the standard RAM-OP questionnaire.
indicators: A character vector of indicator set names. The vector may include one or more of the following: "demo", "food", "hunger", "disability", "adl", "mental", "dementia", "health", "income", "wash", "anthro", "oedema", "screening", "visual", "misc". Default is all indicator set names.
sex: A character value of "m", "f", or "mf" to indicate whether to report indicators for males, females, or both respectively. Default is "mf" for both sexes.

Value

A tibble::tibble() of older people indicators.

Demographic indicators

Variable	Description
`psu`	Primary sampling unit
`resp1`	Respondent is SUBJECT
`resp2`	Respondent is FAMILY CARER
`resp3`	Respondent is OTHER CARER
`resp4`	Respondent is OTHER
`age`	Age of respondent (years)
`ageGrp1`	Age of respondent is between 50 and 59 years
`ageGrp2`	Age of respondent is between 60 and 69 years
`ageGrp3`	Age of respondent is between 70 and 79 years
`ageGrp4`	Age of respondent is between 80 and 89 years
`ageGrp5`	Age of respondent is between 90 years and older
`sex1`	Male
`sex2`	Female
`marital1`	Marital status = SINGLE
`marital2`	Marital status = MARRIED
`marital3`	Marital status = LIVING TOGETHER
`marital4`	Marital status = DIVORCED
`marital5`	Marital status = SEPARATED
`marital6`	Marital status = OTHER
`alone`	Respondent lives alone

Dietary intake indicators

These dietary intake indicators have been purpose-built for older people but the basic approach used is described in:

Kennedy G, Ballard T, Dop M C (2011). Guidelines for Measuring Household and Individual Dietary Diversity. Rome, FAO https://www.fao.org/4/i1983e/i1983e00.htm

and extended to include indicators of probable adequate intake of a number of nutrients / micronutrients.

Variable	Description
`MF`	Meal frequency
`DDS`	Dietary Diversity Score (count of 11 groups)
`FG01`	Cereals
`FG02`	Roots and tubers
`FG03`	Fruits and vegetables
`FG04`	All meat
`FG05`	Eggs
`FG06`	Fish
`FG07`	Legumes, nuts and seeds
`FG08`	Milk and milk products
`FG09`	Fats
`FG10`	Sugar
`FG11`	Other
`proteinRich`	Protein rich foods
`pProtein`	Protein rich plant sources of protein
`aProtein`	Protein rich animal sources of protein
`pVitA`	Plant sources of vitamin A
`aVitA`	Animal sources of vitamin A
`xVitA`	Any source of vitamin A
`ironRich`	Iron rich foods
`caRich`	Calcium rich foods
`znRich`	Zinc rich foods
`vitB1`	Vitamin B1-rich foods
`vitB2`	Vitamin B2-rich foods
`vitB3`	Vitamin B3-rich foods
`vitB6`	Vitamin B6-rich foods
`vitB12`	Vitamin B12-rich foods
`vitBcomplex`	Vitamin B1/B2/B3/B6/B12-rich foods

Household Hunger Scale (HHS)

The HHS is described in:

Ballard T, Coates J, Swindale A, Deitchler M (2011). Household Hunger Scale: Indicator Definition and Measurement Guide. Washington DC, FANTA-2 Bridge, FHI 360 https://www.fantaproject.org/monitoring-and-evaluation/household-hunger-scale-hhs

Variable	Description
`HHS1`	Little or no hunger in household
`HHS2`	Moderate hunger in household
`HHS3`	Severe hunger in household

Katz Index of Independence in Activities of Daily Living score

The Katz ADL score is described in:

Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW (1963). Studies of illness in the aged. The Index of ADL: a standardized measure of biological and psychosocial function. JAMA, 1963, 185(12):914-9 doi:10.1001/jama.1963.03060120024016

Katz S, Down TD, Cash HR, Grotz, RC (1970). Progress in the development of the index of ADL. The Gerontologist, 10(1), 20-30 doi:10.1093/geront/10.4_Part_1.274

Katz S (1983). Assessing self-maintenance: Activities of daily living, mobility and instrumental activities of daily living. JAGS, 31(12), 721-726 doi:10.1111/j.1532-5415.1983.tb03391.x

Variable	Description
`ADL01`	Bathing
`ADL02`	Dressing
`ADL03`	Toileting
`ADL04`	Transferring (mobility)
`ADL05`	Continence
`ADL06`	Feeding
`scoreADL`	ADL Score
`classADL1`	Severity of dependence 1
`classADL2`	Severity of dependence 2
`classADL3`	Severity of dependence 3
`hasHelp`	Have someone to help with everyday activities
`unmetNeed`	Need help but has no helper

K6 Short form psychological distress score

The K6 score is described in:

Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek, DK, Normand SLT, et al. (2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine, 32(6), 959–976 doi:10.1017/S0033291702006074

Variable	Description
`K6`	K6 score
`K6Case`	K6 score > 12 (in serious psychological distress)

Brief Community Screening Instrument for Dementia (CSID)

The CSID dementia screening tool is described in:

Prince M, et al. (2010). A brief dementia screener suitable for use by non-specialists in resource poor settings - The cross-cultural derivation and validation of the brief Community Screening Instrument for Dementia. International Journal of Geriatric Psychiatry, 26(9), 899–907 doi:10.1002/gps.2622

Variable	Description
`DS`	Probable dementia by CSID screen

Health and health-seeking indicators

Variable	Description
`H1`	Chronic condition
`H2`	Takes drugs regularly for chronic condition
`H31`	No drugs available
`H32`	Too expensive / no money
`H33`	Too old to look for care
`H34`	Use traditional medicine
`H35`	Drugs don't help
`H36`	No-one to help me
`H37`	No need
`H38`	Other
`H39`	No reason given
`H4`	Recent disease episode
`H5`	Accessed care for recent disease episode
`H61`	No drugs available
`H62`	Too expensive / no money
`H63`	Too old to look for care
`H64`	Use traditional medicine
`H65`	Drugs don't help
`H66`	No-one to help me
`H67`	No need
`H68`	Other
`H69`	No reason given

Income and income sources

Variable	Description
`M1`	Has a personal income
`M2A`	Agriculture / fishing / livestock
`M2B`	Wages / salary
`M2C`	Sale of charcoal / bricks / etc.
`M2D`	Trading (e.g. market or shop)
`M2E`	Investments
`M2F`	Spending savings / sale of assets
`M2G`	Charity
`M2H`	Cash transfer / Social security
`M2I`	Other

Water, sanitation and hygiene (WASH) indicators

These are a (core) subset of indicators from:

WHO / UNICEF (2006). Core Questions on Drinking-water and Sanitation for Household Surveys. Geneva, WHO / UNICEF https://www.who.int/publications/i/item/9241563265

Variable	Description
`W1`	Improved source of drinking water
`W2`	Safe drinking water (improved source OR adequate treatment)
`W3`	Improved sanitation facility
`W4`	Improved non-shared sanitation facility

Anthropometry and screening

Variable	Description
`MUAC`	Mid-upper arm circumference (mm)
`oedema`	Bilateral pitting oedema (may not be nutritional)
`screened`	Either MUAC or oedema checked previously

Visual impairment by "Tumbling E" method

The "Tumbling E" method is described in:

Taylor HR (1978). Applying new design principles to the construction of an illiterate E Chart. Am J Optom & Physiol Optics 55:348

Variable	Description
poorVA	Poor visual acuity (correct in < 3 of 4 tests)

Miscellaneous indicators

Variable	Description
`chew`	Problems chewing food
`food`	Anyone in HH receives a ration
`NFRI`	Anyone in HH received non-food relief item/s (NFRI) in previous month

Washington Group on Disability

See:

https://www.washingtongroup-disability.com/

for details.

Variable	Description
`wgVisionD0`	Vision domain 0
`wgVisionD1`	Vision domain 1
`wgVisionD2`	Vision domain 2
`wgVisionD3`	Vision domain 3
`wgHearingD0`	Hearing domain 0
`wgHearingD1`	Hearing domain 1
`wgHearingD2`	Hearing domain 2
`wgHearingD3`	Hearing domain 3
`wgMobilityD0`	Mobility domain 0
`wgMobilityD1`	Mobility domain 1
`wgMobilityD2`	Mobility domain 2
`wgMobilityD3`	Mobility domain 3
`wgRememberingD0`	Remembering domain 0
`wgRememberingD1`	Remembering domain 1
`wgRememberingD2`	Remembering domain 2
`wgRememberingD3`	Remembering domain 3
`wgSelfCareD0`	Self-care domain 0
`wgSelfCareD1`	Self-care domain 1
`wgSelfCareD2`	Self-care domain 2
`wgSelfCareD3`	Self-care domain 3
`wgCommunicatingD0`	Communication domain 0
`wgCommunicatingD1`	Communication domain 1
`wgCommunicatingD2`	Communication domain 2
`wgCommunicatingD3`	Communication domain 3
`wgP0`	Overall 0
`wgP1`	Overall 1
`wgP2`	Overall 2
`wgP3`	Overall 3
`wgPM`	Any disability

Examples

# Create indicators dataset from RAM-OP survey data collected from
# Addis Ababa, Ethiopia
create_op(testSVY)
#> ℹ Checking if demo, food, hunger, disability, adl, mental, dementia, health, income, wash, anthro, oedema, screening, visual, misc are RAM-OP indicators
#> ✔ All of `indicators` are RAM-OP indicators
#> # A tibble: 192 × 138
#>      psu  sex1  sex2 resp1 resp2 resp3 resp4   age ageGrp1 ageGrp2 ageGrp3
#>    <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>   <dbl>   <dbl>   <dbl>
#>  1   201     0     1     1     0     0     0    67       0       1       0
#>  2   201     1     0     1     0     0     0    74       0       0       1
#>  3   201     1     0     1     0     0     0    60       0       1       0
#>  4   201     0     1     1     0     0     0    60       0       1       0
#>  5   201     0     1     1     0     0     0    85       0       0       0
#>  6   201     1     0     0     1     0     0    86       0       0       0
#>  7   201     1     0     1     0     0     0    80       0       0       0
#>  8   201     0     1     1     0     0     0    60       0       1       0
#>  9   201     1     0     1     0     0     0    62       0       1       0
#> 10   201     0     1     1     0     0     0    72       0       0       1
#> # ℹ 182 more rows
#> # ℹ 127 more variables: ageGrp4 <dbl>, ageGrp5 <dbl>, marital1 <dbl>,
#> #   marital2 <dbl>, marital3 <dbl>, marital4 <dbl>, marital5 <dbl>,
#> #   marital6 <dbl>, alone <dbl>, MF <dbl>, DDS <dbl>, FG01 <dbl>, FG02 <dbl>,
#> #   FG03 <dbl>, FG04 <dbl>, FG05 <dbl>, FG06 <dbl>, FG07 <dbl>, FG08 <dbl>,
#> #   FG09 <dbl>, FG10 <dbl>, FG11 <dbl>, proteinRich <dbl>, pProtein <dbl>,
#> #   aProtein <dbl>, pVitA <dbl>, aVitA <dbl>, xVitA <dbl>, ironRich <dbl>, …
create_op(testSVY, indicators = "demo")
#> ℹ Checking if demo are RAM-OP indicators
#> ✔ All of `indicators` are RAM-OP indicators
#> # A tibble: 192 × 20
#>      psu  sex1  sex2 resp1 resp2 resp3 resp4   age ageGrp1 ageGrp2 ageGrp3
#>    <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>   <dbl>   <dbl>   <dbl>
#>  1   201     0     1     1     0     0     0    67       0       1       0
#>  2   201     1     0     1     0     0     0    74       0       0       1
#>  3   201     1     0     1     0     0     0    60       0       1       0
#>  4   201     0     1     1     0     0     0    60       0       1       0
#>  5   201     0     1     1     0     0     0    85       0       0       0
#>  6   201     1     0     0     1     0     0    86       0       0       0
#>  7   201     1     0     1     0     0     0    80       0       0       0
#>  8   201     0     1     1     0     0     0    60       0       1       0
#>  9   201     1     0     1     0     0     0    62       0       1       0
#> 10   201     0     1     1     0     0     0    72       0       0       1
#> # ℹ 182 more rows
#> # ℹ 9 more variables: ageGrp4 <dbl>, ageGrp5 <dbl>, marital1 <dbl>,
#> #   marital2 <dbl>, marital3 <dbl>, marital4 <dbl>, marital5 <dbl>,
#> #   marital6 <dbl>, alone <dbl>
create_op(testSVY, indicators = "hunger", sex = "m")
#> ℹ Checking if hunger are RAM-OP indicators
#> ✔ All of `indicators` are RAM-OP indicators
#> # A tibble: 79 × 6
#>      psu  sex1  sex2  HHS1  HHS2  HHS3
#>    <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1   201     1     0     1     0     0
#>  2   201     1     0     1     0     0
#>  3   201     1     0     0     1     0
#>  4   201     1     0     1     0     0
#>  5   201     1     0     0     0     1
#>  6   202     1     0     1     0     0
#>  7   202     1     0     0     1     0
#>  8   202     1     0     1     0     0
#>  9   202     1     0     1     0     0
#> 10   202     1     0     0     1     0
#> # ℹ 69 more rows