5 Chronic diseases

This section explores the relationship between different types of chronic disease and labour market participation. It begins by reporting basic descriptive statistics and then summarises the results from the logistic regression models. The analysis in this section is based on pooled cross-sectional data analysis. As previously mentioned, it should be remembered that words such as “impact” and “effect” are used to describe relationships but do not attempt to denote causation and that theresults of the standard logistic regression models are subject to potential endogeneity bias. Full tables of results from the main models, including unweighted means and standard deviations for the variables, can be found in Appendix D where the reference categories are labelled.

5.1  Chronic disease and labour market participation

Table 1 shows the proportion of the sample with various disease diagnoses. The results indicate that around half of the sample has been diagnosed with one or more chronic diseases.[15] Table 1 indicates that the most common disease is asthma with 18.5% of respondents having been diagnosed with this disease at some point. The rarest disease is a stroke with only 1% of respondents having been diagnosed with a stroke. This small disease prevalence is not surprising given that strokes are likely to be quite rare for those of working age, the group being analysed. Further, stroke is one disease that is more likely to result in death for this group. In other words, for some diseases the prevalence is higher than others as a result of being more likely to survive with the disease (survivor bias).

Source: SoFIE Waves 1-3 Version 4, standard longitudinal weights (*adjusted longitundial weight), Statistics New Zealand.

Note: Results are for those aged 15-64 and who are not full-time students. Data for all three waves is pooled together to create an average rate.

Table 2 shows the labour market participation rates by disease presence. The observed labour market participation rates are considerably lower for those with a disease diagnosis compared to the overall participation rate. Participation is lowest for those who have suffered from a stroke. About half (54%) of people with a diagnosed stroke participate in the labour market, compared to the average participation rate of 83%, a reduction in the likelihood of participation of 35% (29 percentage points). However, this estimate is subject to a larger error given it is based on a relatively small group. Only 1% of the sample reported ever being told by a doctor they had suffered a stroke.

Source: SoFIE Waves 1-3 Version 4, standard longitudinal weights (*adjusted longitudinal weights), Statistics New Zealand

Notes:

1. See note on Table 1.

2. This is just a crude particaption rate. It had not been age standardised.

3. Counts may not sum to totals owing to rounding.

The bivariate analysis in Table 2 above, while interesting, does not control for other factors that may be related to participation. Pooled cross-sectional logistic regressions were used to determine the relationship between disease presence and participation when some other factors were controlled for.

Initially a basic model was conducted including a summary chronic disease indicator (rather than the individual chronic diseases) to determine the overall impact of having chronic disease on participation. Results show that, even after controlling for other variables, the relationship between chronic disease presence and participation is significant (Appendix Table D1). Figure 3 shows that the odds of participating in the labour force are reduced by 31.5% for those with any chronic disease(s).[16] When all variables are fixed at their mean value, the probability of participating is 0.885. This is above the unconditional mean participation rate of 0.827, perhaps because of the more rapid decline in participation for those over 50 years of age which reduces the unconditional average. For those with no chronic diseases, the estimated probability of participating is 0.903, while for those with a chronic disease the estimated probability is reduced to 0.865; a marginal effect of -0.038 (Table 3). This suggests that for an average person, having chronic diseases reduces labour market participation by 3.8 percentage points on average, or 4.3% in a relative sense.

By contrast, the bivariate analysis in Table 2 indicated a difference of 5.8 percentage points. This suggests that other differences in characteristics are important in explaining the lower participation rate of those diagnosed with a chronic disease (Table 2). For example, the odds of participating are lower for: females with young children (this is associated with a reduction in the odds of participating of 90%); those with non-working partners or no partner (75% and 65% reduction respectively); and for females (22% reduction).

Next, models were considered that included variables for each individual disease, rather than a summary variable indicating disease presence. Figure 3 shows the estimated ratio of the odds of labour market participation for those with each disease to the odds for those without each disease. An odds ratio greater than one indicates a positive effect, whilst one between zero and one indicates a negative effect on the odds of participation for those with each disease. If the vertical line for each bar, showing the 95% confidence interval for the odds ratio, crosses one (indicated by the horizontal 95% significance line), then the chance of participation for those with the disease is not significantly different from those without the disease at the 95% level (once other factors are controlled for). Therefore there was insufficient evidence that those with an asthma, high cholesterol, migraine or cancer diagnosis were any less likely to be participating in the labour market than those without these diseases, once other factors were controlled for. For asthma, migraine and high cholesterol this may be a result of such diseases typically being manageable once identified and therefore not inhibiting labour market participation in many cases.

Having been diagnosed with any of the following diseases (in order of impact from highest to lowest) is associated with a significantly reduced odds of labour market participation compared to someone without the disease, once other factors are controlled for:

• psychiatric conditions (are associated with a 70% reduction in the odds of labour market participation for males and 40% for females)
• stroke (59% reduction);
• heart disease (48% reduction);
• diabetes (42% reduction)
• high blood pressure (16% reduction).

For some of these, the presence of the particular reported condition may not itself be associated with lower odds of participating. Rather, other secondary diseases related to the primary disease may be causing the association. For example, high blood pressure may not be associated with reduced odds of participating, but kidney failure resulting from high blood pressure may. Further, collinearity between these health conditions is not formally investigated here.