Income and wealth

Income and wealth

LASA filenames:

Contact: Dorly Deeg


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 ( 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.


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
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)
LASAB019 / LASAC019 / LASAD019 / LASAE019 / LAS2B019 / LASAF019 / LASAG019 / LASAH019 / LAS3B019 / LASMB019 / LASAI019 / LASAJ019 / LASAK019 (J and K not available yet)

Availability of information per wave1:


House ownership
Income amount
Income sources
(LASAB217, LAS2B017
Evaluation of income

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).



  1. Diez Roux AV, Mair C. Neighborhoods and health. Ann NY Acad Sci 2010; 1186: 125-145.
  2. 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.
  3. 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.
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  5. Mansvelt J, Breheny M, Stephens C. Pursuing security: economic resources and the ontological security of older New Zealanders. Ageing Soc 2014; 34: 1666-1687.
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  7. Organisation for Economic Co-operation and Development (OECD). What Are Equivalence Scales? Paris: OECD, 2018. Available at
  8. Statistics Netherlands. Consumer prices; price index 1900 = 100 (Table number 71905eng). Most recent change: 9 February 2023.




Date of last update: June, 2023