Income and wealth
LASA filenames:
LASA015
LASA017
LASA019
Contact: Dorly Deeg
Background
Income is generally obtained from labour. If people cannot work or cannot find work, in the Netherlands they are entitled to certain social security benefits depending on their situation. In older age (up to 2013 starting from age 65, from 2013 onwards from rising ages), all Dutch citizens are entitled to state pension. In addition, many people have savings which may yield regular interest. Income and savings are aspects of the wider concept of wealth, which also includes possession of goods or real property such as home ownership. Income and wealth may be important in terms of explaining behaviour of humans. Over and above their actual income, people’s own evaluations of their income level may be a strong explanatory factor as well (Mansvelt et al 2014). Likewise, the average income level of the neighbourhood in which older people live, is likely to be linked to their behaviour and well-being (Diez Roux & Mair 2010).
Income is one of several indicators of socio-economic position (SEP). Other indicators are level of education, occupational level, housing tenure (see LASA documentation on SES and Housing). While SEP in general is of influence on (changes in) functioning with ageing, each indicator may differentially affect specific aspects of functioning (Kok et al 2016). Income may be particularly linked to worse psychological functioning through financial stress, to physical disability through higher (perceived) barriers to the use of healthcare facilities (Matthews et al 2006), and to social participation (Lynch et al 1997).
Measurement of income in LASA*017
Information on net monthly household income was initially asked in 13 categories, ranging from less than €454 to €2268 or more (up to 2001 when the euro was introduced: from less than Dfl 1000 to Dfl 5000 or more). In 2008 (LASA G-wave) the number of categories was extended to 24, with € 5445 or more as the highest category. This was necessary because the highest category did not only include the very highest incomes anymore, but also incomes in the mid-range, due to cumulative inflation. In order to make calculations with this categorical variable, the code for each category is substituted with the amount of household income at its midpoint. For calculating the midpoint in the highest category, which has no upper limit, the amount is set at the lower limit of this category plus the width of the previous category (*inccat_mid, see syntax attached, point 1).
It depends on the household composition if this income is available to one individual, or is shared with a partner. Thus, if the respondent has a partner, the partner’s income is asked as well, and the categorical income variable reflects the net household income and not just the participant’s income. In order to make income comparable among all respondents, the midpoint amount of each income category is multiplied by 0.7 (more specifically, divided by the square root of two) for respondents who indicated that they have a partner living in their household (*inccat_pcor, see syntax attached, point 2). This correction makes all incomes equivalent to one-person household incomes (OECD 2018). This is also the ratio in Dutch state pensions for citizens living alone and living with others.
When studying changes in income over time, the inflation needs to be taken into account. The rate of inflation fluctuates over the years, with since 1993 the maximum inflation observed at 10.0% in 2022, and the minimum at 0.3% in 2016. Yearly inflation rates are indicated by the Consumer Price Index (CPI), available from Statistics Netherlands (opendata.cbs.nl/statline). For inflation adjustment, a base year needs to be chosen. This may be 1993, the baseline year of the first LASA-cohort. Alternatively, this may be the most recent year included in a particular study. The latter has the advantage that amounts correspond to more recent experience of price levels. However, when studying change over time, change usually is observed prospectively from a starting point that is the earliest observation. In case the base year is the earliest cycle, the amount at the next cycle is divided by the inflation rate at each intervening year (e.g. with an inflation rate of 2.5%, the amount for the first intervening year is divided by 1.025, see syntax attached). Conversely, in case the last year of the study period is chosen as the base year, the amount at the previous cycle is multiplied by the inflation rate at each intervening year (again, with an inflation rate of 2.5%, the amount for the one-before-last year is multiplied by 1.025, and so on).
Income data may have a substantial number of missing values. Missing income data at a certain measurement cycle can be imputed using income from the first subsequent cycle available, or in cycles later than baseline, from the last previous cycle. Imputation needs to be done accounting for inflation.
Lower income limit
It may be relevant to calculate proportions of older people who have an income below a certain limit. This may occur when there is no full entitlement to state pension, i.e., when citizens have lived in the Netherlands during less than 50 years, or when there is no additional pension to the state pension. Therefore, since 2005, the LASA-interview included an additional question about whether the income of the respondent is lower or higher than the so-called “not much but sufficient” limit (nmbs-limit). The definition of this limit is derived from the Social and Cultural Planning Office (Goderis et al 2018, Hoff et al 2019). It is slightly higher than the poverty limit, which is the income considered to cover basic needs (e.g., food, clothing, housing), because it additionally covers a minimum of leisure and social participation needs. The table below provides the nmbs-limit for each LASA-wave since 2005 (in euros per month) for one-person households and for households shared with a partner.
Table. Lower income (not much but sufficient) limit* for each year since 2005 (in euros per month) by household type
No partner in household | Partner in household | |
LASA-f, 2005-2006 | 935 | 1,335 |
LASA-g, 2008-2009 | 976 | 1,340 |
LASA-h, 2011-2012 | 1,040 | 1,425 |
LASA-3b, 2012-2013 | 1,040 | 1,425 |
LASA-i, 2015-2016 | 1,060 | 1,450 |
LASA-j, 2018-2019 | 1,135 | 1,555 |
LASA-k, 2021-2022 | 1,201 | 1,645 |
* Based on Goderis et al. (2018)
Measurement of income evaluation LASA*019
Evaluation of income measures satisfaction with income and perceived income stability. Income satisfaction is indicated by two items: satisfaction with income level and satisfaction with living standard, each with five response categories ranging from very dissatisfied to very satisfied. Both items can be summed to a score ranging from 0 to 8.
Perceived income stability is indicated by two items: having experienced a decline in income of at least € 100 in the preceding 5 years, and expecting a decline in income, each with two response categories: 0=yes, 1=no. These items can be summed to a score ranging from 0 to 2, with a higher score indicating greater stability.
Measurement of wealth in LASA*015
One aspect of wealth is home ownership. In each LASA wave, questions are asked whether the respondents rent or own their home (var=HOWNER), and in the latter case, if the home is free from mortgage (var=MORTGA).
Measurement of neighbourhood income
Neighbourhood characteristics are gathered in the GECCO project (Timmermans et al 2018). This includes geo-data at address-level, 6-digit postal code-level, 4-digit postal code-level or neighbourhood-level from different sources on: population and households, socioeconomic status, air pollution, road-traffic, rail-traffic and air-traffic noise, liveability, neighbourhood environment, and urbanisation grade.
Questionnaires
LASAB015 / LASAC015 / LASAD015 / LASAE015 / LAS2B015 / LASAF015 / LASAG015 / LASAH015 / LAS3B015 / LASAI015 / LASAJ015 / LASAK015 (main interview, in Dutch)
LASAB017 / LASAC017 / LASAD017 / LASAE017 / LAS2B017 / LASAF017 / LASAG017 / LASAH017 / LAS3B017 / LASMB017 / LASAI017 / LASAJ017 / LASAK017 (main interview, in Dutch)
LASAB019 / LASAC019 / LASAD019 / LASAE019 / LAS2B019 / LASAF019 / LASAG019 / LASAH019 / LAS3B019 / LASMB019 / LASAI019 / LASAJ019 / LASAK019 (main interview, in Dutch)
Variable information
LASAB015 / LASAC015 / LASAD015 / LASAE015 / LAS2B015 / LASAF015 / LASAG015 / LASAH015 / LAS3B015 / LASMB015 / LASAI015 / LASAJ015 / LASAK015
(pdf)
LASAB017 / LASAC017 / LASAD017 / LASAE017 / LAS2B017 / LASAF017 / LASAG017 / LASAH017 / LAS3B017 / LASMB017 / LASAI017 / LASAJ017 / LASAK017 (J and K not available yet);
LASAB217 (income specification; in wave 2B these data were processed in LAS2B017)
(pdf)
LASAB019 / LASAC019 / LASAD019 / LASAE019 / LAS2B019 / LASAF019 / LASAG019 / LASAH019 / LAS3B019 / LASMB019 / LASAI019 / LASAJ019 / LASAK019 (J and K not available yet)
(pdf)
Availability of information per wave1:
B | C | D | E | 2B* | F | G | H | 3B* | MB* | I | J | K | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
House ownership (LASA015) | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | - | Ma | Ma | Ma | |
Income amount (LASA017) | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | |
Income sources (LASAB217, LAS2B017 | Ma | - | - | - | Ma | - | - | - | - | - | - | - | - | |
Evaluation of income (LASA019) | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | Ma | |
¹ More information about the LASA data collection waves is available here
* 2B=baseline second cohort;
3B=baseline third cohort;
MB=migrants: baseline first cohort;
LASA017, LASA019: J, K=not available yet
Ma=data was collected in main interview
Previous use in LASA
Income has been used mainly as a determinant of a range of subsequent outcomes including changes in physical functioning (Broese van Groenou et al 2003, Koster et al 2006a), depression (Koster et al 2006b, Motoc et al 2019), frailty (Hoogendijk et al. 2018), health behaviour (Comijs et al 2012, Dijkstra et al 2014, 2015), successful ageing (Kok et al 2016), use of care services (Geerlings et al 2005, Schuijt-Lucassen & Broese van Groenou 2006, DaRoit & Thomese, 2016, Jacobs et al. 2018), medication use (Sonnenberg et al 2012), residential relocation (Bloem et al 2008) and social participation (Lamme et al 1998). Income has also been used as one of the descriptive characteristics of specific groups, such as older people with ADHD (Michielsen et al 2015) and resident caregivers (Visser et al 2004). One study involved discrepancies between personal income and neighbourhood status (Deeg & Thomése 2005), one study used income as an explanatory factor of the association between education and frailty (Hoogendijk et al 2014), and one study defined income as a resilience factor in the disablement process (Klokgieters et al. 2018).
Evaluation of income (or subjective income) has been used much less often. One study included the two variables as potential mediators of the association between neighbourhood status and health (Deeg & Thomése 2005). It was furthermore studied as a determinant of leisure activities (Galenkamp et al. 2016) and of transnational behaviour of migrants (Klok et al 2017).
Home ownership has been used as an indicator of wealth in a study of working past retirement (Deeg et al 2018).
- Bloem BA, Van Tilburg TG, Thomése GCF. Residential mobility in older Dutch adults: Influence of later life events. Int J Ageing Later Life 2008; 1(3): 21-44. *Retirement, an empty nest, widowhood and a decline in health each triggered specific moves. In additional analyses, the effects of triggers, especially health changes, were moderated by conditions including income.*
- Broese van Groenou MI, Deeg DJH, Penninx BWJH. Income differentials in functional disability in old age: Relative risks of onset, recovery, decline, attrition and mortality. Aging Clin Exp Res 2003; 15: 174-183. *Income inequality in health in late life is to a large degree explained by the higher incidence of disability among lower-income women and by the higher attrition and mortality risks among lower-income men.*
- Comijs HC, Aartsen MJ, Visser M, Deeg DJH. Alcohol consumption among persons aged 55+ in the Netherlands. Tijdschr Gerontol Geriatr 2012; 43: 115-126. In Dutch. *Heavy and binge drinking is more likely in older people with higher income.*
- DaRoit B, Thomese F. Maakt lokale thuiszorg zorg (on)gelijker? Sociaaleconomische ongelijkheid in de toegang tot huishoudelijke zorg binnen Nederlandse gemeenten voor en na de invoering van de WMO in 2007 [Does local home care increase (in)equality? Socioeconomic inequality in the access to home care in Dutch municipalities before and after the introduction of the Social Support Act in 2007]. Mens & Maatschappij 2016; 91 (4): 381-403. *After decentralization of professional home care in 2007, low income older adults received home care more often than those with higher incomes.*
- Deeg DJH, Thomése GCF. Discrepancies between personal income and neighbourhood status: Effects on physical and mental health. Eur J Ageing 2005; 2: 98-108.*Discrepancies between personal income and neighbourhood status, accrued throughout the life course, are associated with poor health.*
- Deeg D, van der Noordt M, van der Pas S. Two decades of working beyond age 65 in the Netherlands. Health trends and changes in socio-economic and work factors to determine the feasibility of extending working lives beyond age 65. Netspar Design Paper 89, November 2017. *Home ownership with a mortgage still to be paid off was associated with working after statutory retirement age.*
- Dijkstra SC, Neter JE, Brouwer IA, Huisman M, Visser M. Adherence to dietary guidelines for fruit, vegetables and fish among older Dutch adults; the role of education, income and job prestige. J Nutr Health Aging 2014; 18(2): 115-121. *Education and income have independent and unique contributions to adherence to healthy diets.*
- Dijkstra SC, Neter JE, Van Stralen MM, Knol DL, Brouwer IA, Huisman M, Visser M. The role of perceived barriers in explaining socio-economic status differences in adherence to the fruit, vegetable and fish guidelines in older adults: a mediation study. Public Health Nutr 2015: 18(5): 797-808. *Cost concerns explained the lower adherence to the guidelines for fruit and fish in lower-income groups in older adults*
- Galenkamp H, Gagliardi C, Principi A, Golinowska S, Moreira A, Schmidt AE, Winkelmann J, Sowa A, Van der Pas S, Deeg DJH. Predictors of social leisure activities in older Europeans with and without multimorbidity. Eur J Ageing 2016; 13: 129-143. *Subjective income was associated with leisure activities only in older persons without multimorbidity.*
- Geerlings SW, Pot AM, Twisk JWR, Deeg DJH. Predicting transitions in the use of informal and professional care by older adults. Ageing Soc 2005; 25: 111-130. *Income played a role in several transitions towards higher levels of long-term care.*
- Hoogendijk EO, Heymans MW, Deeg DJH, Huisman M. Socioeconomic inequalities in frailty among older adults: results from a 10-year Longitudinal Study in the Netherlands. Gerontology 2018; 64: 157-164. *Lower income groups had a higher prevalence of frailty, but this income difference in frailty did not increase over time.*
- Hoogendijk E, Van Hout HPJ, Heymans MW, Van der Horst HE, Frijters DHM, Broese van Groenou MI, Deeg DJH, Huisman M. Explaining the association between educational level and frailty in older adults: results from a 13-year longitudinal study in the Netherlands. Ann Epidemiol 2014: 24: 538-544. *Part of the educational inequality in frailty was attributed to income*
- Jacobs MT, Broese van Groenou MI, Aartsen MJ, Deeg DJH. Diversity in older adults’ care networks: the added value of individual beliefs and social network proximity. J Gerontol B Psychol Sci Soc Sci 2018; 73(2): 326-336. *Older care receivers with a low income were likely to have a publicly paid care network.*
- Klok J, Van Tilburg TG, Suanet BA, Fokkema CM. Transnational aging among older Turkish and Moroccan migrants in the Netherlands: Determinants of transnational behavior and transnational belonging. Transnat Soc Rev 2017; 7: 25-40. *Subjective income, but not income itself, impacts transnational behaviour in older migrants; neither affect transnational belonging.*
- Klokgieters, SS, Van Tilburg TG, Deeg DJH, Huisman M. Resilience in the disabling effect of gait speed among older Turkish and Moroccan immigrants and native Dutch. J Aging Health 2018; 30 (5): 711-737. *The resilience factor income buffered the association of physical impairment and disability among Dutch, but not among immigrant older adults.*
- Kok A, Aartsen MJ, Deeg DJH, Huisman M. Socioeconomic inequalities in a 16-year longitudinal measurement of successful ageing. J Epidemiol Comm Health 2016; 70: 1106-1113. *Unique contributions of education, occupation and income to inequalities in successful ageing.*
- Koster A, Bosma H, Broese van Groenou MI, Kempen GIJM, Penninx BWJH, Van Eijk JThM, Deeg DJH. Explanations of socioeconomic differences in changes in physical function in older adults: results from the Longitudinal Aging Study Amsterdam. BMC Public Health 2006a; 6: 244, 1-12. *In 55-70-year-olds, there was an income differential in decline in physical function, while income differentials did not further widen in participants aged 70 years and older.*
- Koster A, Bosma H, Kempen GIJM, Penninx BWJH, Beekman ATF, Deeg DJH, Van Eijk, JThM. Socioeconomic differences in incident depression in older adults: the role of psychosocial factors, physical health status, and behavioral factors. J Psychosom Res 2006b; 61: 619-627. *Incidence of depression was significantly higher in participants with low income.*
- Lamme SP, Linnemann MA, Deeg DJH, Schuyt TNM. Armoede, sociale participatie en eenzaamheid bij ouderen [Poverty, social participation and loneliness in older persons]. In G. Engbersen, J.C. Vrooman, E. Snel (Eds.), Effecten van armoede. Derde jaarrapport armoede en sociale uitsluiting [Effects of poverty](pp. 129-227). Amsterdam: University Press, 1998. In Dutch. *Older persons with a low income maintain fewer personal relationships, are less involved in clubs and organizations, and participate less in socio-cultural activities than older persons with a higher income.*
- Michielsen M, Comijs HC, Aartsen MJ, Semeijn E, Beekman ATF, Deeg DJH, Kooij JJS. The relationships between ADHD and social functioning and participation in older adults in a population-based study. J Attention Dis 2015: 19: 368-379. *Older persons with ADHD had lower income than those without ADHD.*
- Motoc I, Timmermans EJ, Deeg DJH, Penninx BWJH, Huisman M. Associations of neighbourhood sociodemographic characteristics with depressive and anxiety symptoms in older age: Results from a 5-wave study over 15 years. Health Place 2019; 59: 102172. *Adjusting for personal income levels, a higher percentage of immigrants and higher urban density, but not other neighbourhood characteristics, were significantly associated with depressive and anxiety symptoms.*
- Schuijt-Lucassen NY, Broese van Groenou MI. Verschillen in zorggebruik door ouderen naar inkomen: De rol van gezondheid, sociale context, voorkeur en persoonlijkheid [Income inequality in the use of professional home care by older adults: The impact of health, social context, care preference and personality]. Tijdschr Soc Geneesk 2006; 84: 4-11. In Dutch. *Older adults with low income were more likely to use professional home care compared to older adults with high income. Poor health contributed most to this income inequality.*
- Sonnenberg CM, Bierman EJM, Deeg DJH, Comijs HC, Van Tilburg W, Beekman ATF. Ten-year trends in benzodiazepine use in the Dutch population. Soc Psychiatr Psychiatric Epidemiol 2012: 47: 293-301. *There was a preponderance of benzodiazepine use in people with low income.*
- Timmermans EJ, Lakerveld J, Beulens JW, Boomsma DI, Kramer SE, Oosterman M, Willemsen G, Stam M, Nijpels G, Deeg DJH, Penninx BWJH, Huisman M. Cohort profile: the Geoscience and Health Cohort Consortium (GECCO) in the Netherlands. BMJ Open 2018; 8: e021597. *Amongst many other environmental characteristics, average income at the neighbourhood level was included for all Dutch municipalities.*
- Visser, G, Klinkenberg M, Broese van Groenou MI, Willems DL, Knipscheer CPM, Deeg DJH. The end of life: informal care for dying older people and its relationship to place of death. Palliat Med 2004; 18: 468-477. *Resident caregivers were disadvantaged in several respects (i.e. health, income, assistance from other carers) compared to non-resident caregivers.*
References
- Diez Roux AV, Mair C. Neighborhoods and health. Ann NY Acad Sci 2010; 1186: 125-145.
- Goderis B, van Hulst B, Wildeboer Schut JM, Ras M. De SCP-methode voor het meten van armoede. Herijking en revisie [The SCP-method of measuring poverty. Recalibration and revision]. The Hague: Social and Cultural Planning Office, 2018. In Dutch.
- Hoff S, van Hulst B, Wildeboer Schut JM, Goderis B. Armoede in kaart [Poverty mapped]. The Hague: Social and Cultural Planning Office, 2019. In Dutch.
- Lynch JW, Kaplan GA, Shema SJ. Cumulative impact of sustained economic hardship on physical, cognitive, psychological, and social functioning. N Engl J Med 1997; 337: 1889–1895.
- Mansvelt J, Breheny M, Stephens C. Pursuing security: economic resources and the ontological security of older New Zealanders. Ageing Soc 2014; 34: 1666-1687.
- Matthews RJ, Jagger C, Hancock RM. Does socio-economic advantage lead to a longer, healthier old age? Soc Sci Med 2006; 62: 2489–2499.
- Organisation for Economic Co-operation and Development (OECD). What Are Equivalence Scales? Paris: OECD, 2018. Available at http://www.oecd.org/els/soc/OECD-Note-EquivalenceScales.pdf.
- Statistics Netherlands. Consumer prices; price index 1900 = 100 (Table number 71905eng). Most recent change: 9 February 2023. https://opendata.cbs.nl/statline#/CBS/en/dataset/71905eng/table?ts=1686054582913
Appendix
Date of last update: June, 2023