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Growing up in Scotland: the circumstances of persistently poor children

Published: 29 Apr 2010

This report looks at how many children experience persistent poverty and which children are most likely to be persistently poor. It also examines the outcomes of children from persistently poor families.

72 page PDF

700.6 kB

72 page PDF

700.6 kB

Contents
Growing up in Scotland: the circumstances of persistently poor children
chapter 3 WHICH CHILDREN ARE MOST LIKELY TO BE PERSISTENTLY POOR?

72 page PDF

700.6 kB

chapter 3 WHICH CHILDREN ARE MOST LIKELY TO BE PERSISTENTLY POOR?

The aim of this chapter is to identify the children most likely to be persistently poor and compare these with children in short-term poverty and those who avoid poverty. Various background characteristics of children are explored, including family size and composition, parents' work status, education, health, tenure and characteristics of the local area. We first provide a descriptive picture of the types of children in each poverty category. We then use multivariate regression analysis to unravel which characteristics are related to an increased risk of persistent poverty when holding other, potentially confounding, characteristics constant.

The key findings from this chapter are:

  • Certain children were more likely than others to experience persistent poverty. These included those in lone-parent families, larger families, families with a young mother, families with parents with low education, and families who live in rented housing, particularly social-rented housing (Section 3.1).
  • Some of these factors may not be driving persistent poverty, they may be consequences of being poor, and for others the relationship with poverty is inherently complex. Multivariate analysis - designed to identify the risk of persistent poverty, while controlling for the impact of possibly confounding influences - shows that family work status is the factor that bears most on the risk of persistent poverty. Being continuously out of work is the key driver of persistent poverty (Section 3.2).

3.1 The types of children most at risk of persistent poverty

This section looks at the risk of poverty duration according to a range of socio-demographic and socio-economic characteristics. Particular attention is paid to identifying the types of children most at risk of persistent poverty. In this section we look descriptively at the association between each characteristic and poverty duration. This provides an early indication of some of the underlying factors that may be linked to persistent poverty.

We identified a number of factors that are likely to be associated with poverty duration, covering socio-demographic background, socio-economic characteristics and features of the local area. Some of these were measured just once during the period under investigation, such as ethnicity. Other factors are more dynamic by nature and we take advantage of the fact that GUS is a longitudinal study to construct measures of change (so called time-varying factors), such as changes in the number of children in the family (perhaps due to a new born or an older child leaving home). Table 3.1, along with the relevant section in Appendix 1, presents a detailed description of all factors and explains how they were measured using the GUS data.

Table 3.1 Factors included in analysis of risk of poverty duration

Variable

Year measured

Categories

Socio-demographic

Sex of child

sweep 1

Boy, Girl

Ethnic group of mother

sweep 1

White, Ethnic minority communities

Age of mother at birth of GUS child

sweep 1

Under 25, 25-29, 30-34, 35 and over

Family type transitions

sweep 1 to sweep 4

Stable couple, Couple who separated, Stable lone parent, Lone parent who re-partnered

Number of children at Sweep 1

sweep 1

1, 2, 3 or more

Change in the number of children

sweep 1 to sweep 4

No change, Increase, Decrease

GUS child is mother's firstborn

sweep 1

Yes, No

Mother's health status

sweep 1 and sweep 4

No health problems (at sweeps 1 or 4), Reduced health problems (at sweep 1 but not at sweep 4), Developed health problems at (not at sweep 1 but at sweep 4), Persistent health problems (at both sweep 1 & 4)

Socio-economic

Average Work Intensity

sweep 1 to sweep 4

A measure of household employment. See Appendix 1 for detailed description

Mother's education

sweep 1

Higher grade or above, Standard grade or lower

Father's education

sweep 1

Higher grade or above, Standard grade or lower

Social class at Sweep 1

sweep 1

Managerial/professional, occupations, Intermediate, Small employer/own account, Lower supervisory/technical occupations, Semi-routine and routine occupations, No-one in employment

Family has a car

sweep 1 to sweep 4

At none of the sweeps, At 1-3 sweeps, At all four sweeps

Whether family uses childcare

sweep 1 to sweep 4

Not using at Sweeps 1 & 4, Started using, Stopped using, Using at Sweeps 1 & 4

Tenure

sweep 1

Owner occupier, Social renter, Private renter, Other

Local area

Urbanization

sweep 1

Large urban, Other urban, Towns, Rural

Area deprivation level ( SIMD quintiles)

sweep 1

Least deprived quintile, 2nd quintile, 3rd quintile, 4th quintile, Most deprived quintile

Tables 3.2 - 3.4 present the risk of poverty duration for each group of factors. The results are presented separately for the birth and child cohorts. However, since the patterns of associations are generally very similar for both cohorts, we do not refer to specific cohorts when describing the results (unless the cross-cohort differences are significant).

Table 3.2 presents the risk of poverty duration by socio-demographic background. There are no differences with respect to the sex of the child but children from ethnic minority communities are more at risk of persistent poverty than White children. 17 Children with young mothers (under 25) faced a higher risk of persistent poverty than those with older mothers; as did those that had lived in a lone-parent family at any time during the observation period (compared to those permanently living in a couple family).

Table 3.2 Risk of poverty duration by socio-demographic background Row % (per cohort)

Birth cohort

Child Cohort

Not poor

Temporarily poor

Persistently poor

Unweighted count

Not poor

Temporarily poor

Persistently poor

Unweighted count

Sex of child

Boy

59

17

24

1,817

60

20

20

959

Girl

58

19

23

1,715

60

20

20

921

Ethnic group of mother

White

59

18

23

3,452

60

20

20

1,838

Ethnic minority

34

17

49

80

44

13

44

42

Age of mother at birth of GUS child

Under 25

22

27

50

625

28

34

39

345

25-29

61

19

20

816

59

21

19

423

30-34

74

13

12

1,243

75

13

12

671

35 and over

72

14

14

848

75

12

13

441

Family type transitions

Stable couple

73

15

12

2,883

76

15

9

1,471

Couple who split up

30

30

39

159

34

36

30

68

Lone parent who partnered

13

38

49

158

16

44

40

98

Stable lone parent

7

20

73

332

14

27

59

243

Number of children at sweep 1

1

62

18

21

1,650

61

23

16

612

2

62

18

20

1,253

65

19

16

870

3+

44

19

37

629

46

18

35

398

Change in the number of children

No change

58

19

23

2,251

62

20

18

1,340

Increase

62

16

21

1,143

59

19

22

444

Decrease

27

24

49

138

36

21

43

96

GUS child is mother's firstborn

No

56

18

25

1,831

58

19

23

1,006

Yes

60

18

22

1,701

62

21

17

874

Mother's health status

No health problems

62

18

21

2,624

63

19

17

1,379

Reduced health problems

50

21

29

233

50

20

31

130

Developed health problems

50

19

31

369

57

19

24

185

Persistent health problems

45

19

36

306

46

24

29

186

All

58

18

24

3532

60

20

20

1880

Children in stable lone-parent families were in the family type most at risk of persistent poverty. For example, 73 per cent of birth-cohort children who were in lone-parent families throughout the period were persistently poor, compared with only 12 per cent of children from stable couple-families. Children from larger families also faced a higher risk of persistent poverty as did children whose mother reported health problems or disability, particularly if these were longer-term.

Table 3.3 looks at socio-economic factors. As expected, socio-economic status of the main earner is a very strong predictor of persistent poverty. Virtually all families where no-one was in employment were poor at some point, and about 8 out of 10 of such families experienced persistent poverty. Among the families where the main earner was employed, the risk of persistent poverty decreased in line with increases in socio-economic status of the job. For example, only about 3 per cent of the families where the main earner was employed in a professional/managerial job experienced persistent poverty, compared with about a quarter of the families where the main earner had a semi-routine or routine occupation.

Similarly, the average work intensity ( AWI) 18 in the household strongly shapes the risk of persistent poverty and poverty in general. Only about 10 per cent of families where all adults worked full-time for virtually the whole period under investigation ( AWI>75%) were affected by any form of poverty, and only 1 per cent of such families experienced persistent poverty. The results were almost as low in the case of the families with AWI in the range 51-75%. Families with AWI of 26-50% had markedly higher risks of persistent poverty - about half of such families experienced poverty at some point and one in five were persistently poor. As expected, the families who only used up to a quarter of their workforce potential faced highest risk of poverty: almost 9 out of 10 such families lived in persistent poverty and virtually all of the remaining 10 per cent experienced temporary poverty at some point between 2005/06 and 2008/09.

It is evident that the risk of persistent poverty is related to parent's education: Higher grades or above offers a good protection against persistent poverty both in the case of mothers' and fathers' education. Ownership of a car was also linked to the risk of persistent poverty (although this, like other factors, could also be an outcome of poverty). Also, families who did not use childcare faced persistent poverty. This could be for a variety of reasons; including having one parent at home caring for a very young child who looks after the family through choice or being constrained by uneconomical childcare costs. Finally, social renters faced a higher risk of persistent poverty than private renters and owner-occupiers.

Table 3.3 Risk of poverty duration by socio-economic background Row % (per cohort)

Birth cohort

Child Cohort

Not poor

Temporarily poor

Persistently poor

Unweighted bases

Non poor

Temporarily poor

Persistently poor

Unweighted bases

Mother's education

Higher grade or above

70

16

14

2,755

69

18

13

1,466

Standard grade or lower

28

24

49

777

31

26

42

414

Father's education

Higher grade or above

69

17

14

2,590

69

17

14

1,393

Standard grade or lower

34

21

45

942

37

27

37

487

Social class at sweep 1

Managerial/professional

87

10

3

1,434

88

9

3

753

Intermediate occupations

65

22

13

263

66

29

5

139

Small employer/own account

60

23

18

334

65

23

12

176

Lower supervisory/ technical occupations

68

21

11

473

69

25

7

246

Semi-routine and routine occupations

45

28

27

621

48

29

23

330

No-one in employment

0

18

81

407

2

24

75

236

Average work intensity 19

76-100%

89

10

1

623

89

9

1

348

51-75%

80

16

4

1,316

81

15

4

659

26-50%

47

30

22

685

49

32

19

378

0-25%

1

10

89

327

1

15

85

173

Family has a car

At all four sweeps

73

16

10

2,877

75

16

9

1,540

At 1-3 sweeps

17

32

51

343

17

40

43

167

At none of the sweeps

9

15

76

312

9

24

67

173

Whether family uses childcare

Both at sweep 1 & 4

68

17

15

2,022

68

18

14

1,250

At sweep 1 but not at sweep 4

46

18

36

208

60

20

19

262

At sweep 4 but not at sweep 1

52

22

26

768

37

27

36

219

Neither at sweep 1 nor at sweep 4

37

18

45

534

32

24

43

149

Tenure

Owner occupier

80

13

6

2,526

82

14

4

1,353

Social renter

14

27

59

732

15

34

51

393

Private renter

33

26

41

183

32

24

44

101

Other

31

29

40

91

36

22

42

33

Total

58

18

24

3532

60

20

20

1880

Table 3.4 shows the risk of poverty duration by indicators of the local area. Overall, families living in cities faced higher risk of poverty in general, and persistent poverty in particular, than families living in towns or in rural areas. The risk of persistent poverty was proportionate to the area deprivation level, represented by the value of the Scottish Index of Multiple Deprivation characterising the area: the higher the SIMD value, the higher risk of poverty.

Table 3.4 Risk of poverty duration by area indicators Row % (per cohort)

Birth cohort

Child Cohort

Not poor

Temporarily poor

Persistently poor

Unweighted count

Non poor

Temporarily poor

Persistently poor

Unweighted count

Urbanization

Large urban

55

17

28

1,187

57

22

21

593

Other urban

56

19

25

1,180

59

18

23

627

Town

60

20

20

481

63

22

15

279

Rural

67

19

14

684

65

18

16

381

Area deprivation ( SIMD quintiles)

Least deprived

87

9

4

809

87

10

3

451

2

72

17

11

778

74

18

9

444

3

63

18

19

729

61

21

18

393

4

46

22

32

580

46

24

31

284

Most deprived

29

23

48

636

28

28

44

308

Total

58

18

24

3532

60

20

20

1880

3.2 Modelling the key risk factors behind the duration of poverty

Having investigated the separate relationships between the poverty duration and each of the factors, we now turn to multivariate analysis where we include all factors in a single statistical model. The main aim of this analysis is to identify which factors are associated with poverty duration, when accounting for other, potentially confounding, variables. We do so by specifying a statistical model using the poverty categories defined previously - 'no poverty', 'temporary poverty', 'persistent poverty'. Whereas some studies have used multinomial logistic regression for this analysis, we recognize here that the poverty categories are intrinsically ordered and hence we use an ordinal logistic regression model, and compare each poverty category to a 'shorter-duration poor' group ( i.e. comparing short-term poor to those who avoid poverty, and then long-term poor to short-term poor). 20 The factors are represented by the same indicators that were used in the previous section (see Table 3.1 for details). Table A2.1 in Appendix 2 presents the odds ratios from the ordinal logistic models, estimated for each cohort separately. The interpretation of odds ratios is explained in Appendix 1.

It is important to note that the analysis presents significant relationships between the characteristics of families and the risk of persistent poverty - the analysis does not unravel any cause and effect in the relationship. For example, if there is a relationship between tenure and persistent poverty, where families in social rented housing are more likely to experience persistent poverty, the analysis cannot unravel whether living in social rented housing is a cause of persistent poverty. There may also be moderating factors, which may themselves increase the chance of a family experiencing persistent poverty. The main point to note is that the analysis presented here does not provide cause, furthermore respondents were not asked to attribute cause themselves.

Previous research ( e.g. by Adelman et al., (2003), Berthoud et al., (2004), Middleton (2006) and Barnes et al., (2006)) found that factors associated with persistent poverty include work status, ethnicity, health and age. Similar factors were found to play a role in the current research.

Factors significantly associated with persistent poverty in both cohorts were (see Table A2.1 for detail):

  • Work intensity, low average work intensity
  • Socio-economic status, low socio-economic status of the main earner
  • Family type, children that had lived in a lone-parent family at any point during the observation period
  • Age of mother, children with young mothers (under 25)
  • Education, children whose parents (particularly mothers) had a lower level of education
  • Tenure, children who lived in social-rented accommodation
  • Local area, children who lived in deprived areas

Low average work intensity (0-25%) was by far the strongest predictor of increased risk of persistent poverty. This is not surprising, as this level of AWI corresponds to persistently workless families or those with working parents in only one of the four years under investigation on average. Also, socio-economic status of the main earner strongly influenced the risk of persistent poverty: the families where the main earner had lower socio-economic status faced higher risk of a longer experience of poverty than other families.

Some of the factors only had a significant effect in one data cohort. Notably, ethnicity appears to be a highly significant factor in the birth cohort, but not in the child cohort, which may be due to a smaller sample size in the latter case. Families with more than one child faced a higher risk of poverty in the child cohort but not the birth cohort.

Finally, it needs to be noted that some of the results of the regression analysis, such as the effect of decrease in the number of children or the child being the first child in the family, despite being significant are rather difficult to interpret and worthy of further investigation. 21