All Indicators > Indicator SH2: Health capital

Definition	Individuals potential for health across the life course
Dimension	Situation of health
Sector	Health status (individual)
Components	SH2_1 Obesity SH2_2 Blood pressure SH2_3 Cholesterol SH2_4 Low birth weight (for infants)
Source	Various - see component details

Component SH2_1: Obesity

Definition	Modelled estimate of proportion with a Body Mass Index greater than 30. Body Mass Index is calculated from height and weight data (i.e. the ratio of weight (kg)/height (m2))
Source	2001, 2001 Ethnic: Health Survey for England, 1998 to 2001, Joint Survey Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health, University College London / Department of Health (See: Health Survey for England)
	2003: Health Survey for England, 2001 to 2003, Joint Survey Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health, University College London / Department of Health (See: Health Survey for England)
	2005: Health Survey for England, 2003 to 2005, Joint Survey Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health, University College London / Department of Health (See: Health Survey for England)

Additional details

In the absence of any suitable administrative or census data, survey data was the only source of information available to construct an indicator of obesity. However there are a number of problems associated with using survey data to produce Local Authority District (LAD) estimates, including small or non-existent samples in some areas leading to large variances and unstable estimates and biases introduced by particular sampling strategies.

A great deal of work, particularly in the last twenty years, has gone into addressing these issues. Although a number of different approaches have been used, all the methods tend to fall somewhere on a continuum between using direct estimates, suitably weighted for sample design, and a modelling approach using local area covariates to estimate the indicator of interest. Some are based on only one or other of the methods. However the two methods each have their own particular problems. Direct estimates, weighted as necessary, are unbiased but may have large variances; on the other hand the modelled estimates will have small variances but will be biased. Hence many estimates attempt to combine information from both in order to solve the common problem of minimising the Mean Square Error of the final estimate.

The method used in the HPI required that a well-fitted micro level model could be identified. It also assumed that the important ways in which a group may have been over-sampled in a survey sample can be captured by covariates available in the survey and at a small area level. It involved combining all surveys available for the required year with the necessary dependent and independent variables (e.g. socio-economic status, age, gender and ethnicity). Data were gathered from the Health Survey for England (HSE) (1998 –2003 ) for estimates for both the whole population and for the ethnic groups.

In 1999, the focus of the HSE was the health of minority ethnic groups as a means to increase understanding through the monitoring of trends that will enable us to make predictions. For this purpose a boost sample was designed in order to yield interviews with members of the most populous six minority ethnic groups: Black Caribbean, Indian, Pakistani, Bangladeshi, Chinese, and Irish. For the purpose of this estimate, Irish is included under White, and the Black African group added (although this sample was not boosted, hence the low numbers). The table below shows the number of ethnic groups available for each year that were used in the modelling of estimates for ethnic groups:

		Year				Total
		1998	1999	2000	2001	Total
Ethnic Group	White	18019	10437	8851	17322	54629
	Black Caribbean	183	2029	143	296	2651
	Black African	143	73	98	172	486
	Indian	321	1909	203	287	2720
	Pakistani	198	2148	91	225	2662
	Bangladeshi	73	1905	64	83	2125
	Chinese	39	961	17	37	1054
Total		18796	19462	9467	18422	66327

Only the main, adult sample, and not the oversampled ‘special populations’, was included in the modelling process for the whole population. For the ethnic population estimates, the adult and 1999 ethnic minority boost was used.

Step 1
Using combined survey data, with LAD geocoding, a multi-level, variable intercepts, logistic model was run, with level one being the individual i, level two the primary sampling unit j and level three the LAD k. Covariates from within the survey, shown in lower case, and LAD level data, shown in upper case, were used to predict the individual level behaviour.

Logit (Pijk) = Xijk B + Ujk + Vk + Eijk

Where P is a vector of probabilities associated with individual i in Primary Sampling Unit (PSU) j within LAD k, B a vector of regression coefficients, X a matrix of covariates associated with the individual measured within the survey, U a random vector of area effects associated with the PSU and V the LAD and E is a vector of independent random 'noise' elements. The matrix of covariates included PSU area measures, based on aggregated individual level survey counts within the PSU. These covariates are given in the table below:

2001 Total Population - Obesity
		Covariates
	Constant	-1.980
Individual effects	20-24 years	0.547
	25-29 years	0.927
	30-34 years	1.150
	35-39 years	1.306
	40-44 years	1.271
	45-49 years	1.467
	50-54 years	1.610
	55-59 years	1.608
	60-64 years	1.714
	65-69 years	1.660
	70-74 years	1.599
	75+ years	1.213
	Male	-0.160
	Social class I, II and IIIA	-0.248
	Income Support recipient	0.240
PSU area effects	Proportion Black	0.582
	Proportion Asian	-0.308
	Proportion higher social class	-0.318
	Proportion living alone	-0.631
LAD area effects	Proportion higher social class	-1.123

2001 Ethnic Groups - Obesity
		Covariates
	Constant	-2.56
Individual effects	Bangladeshi	-1.09
	Black African	0.058
	Black Caribbean	0.292
	Chinese	-1.49
	Indian	-0.236
	Pakistani	0.051
	20-24 years	0.531
	25-29 years	0.862
	30-34 years	1.103
	35-39 years	1.275
	40-44 years	1.236
	45-49 years	1.435
	50-54 years	1.558
	55-59 years	1.571
	60-64 years	1.665
	65-69 years	1.612
	70-74 years	1.553
	75+ years	1.177
	Male	-0.203

2003 Total Population - Obesity
		Covariates
	Constant	-1.934
Individual effects	20-24 years	0.736
	25-29 years	0.803
	30-34 years	1.223
	35-39 years	1.294
	40-44 years	1.344
	45-49 years	1.452
	50-54 years	1.600
	55-59 years	1.520
	60-64 years	1.677
	65-69 years	1.641
	70-74 years	1.532
	75+ years	1.213
	Male	-0.074
	Higher social class	-0.213
	Income Support recipient	0.192
PSU Area Effects	Proportion Asian	-0.233
	Proportion higher social class	-0.482
	Proportion living alone	-0.265
LAD area effects	Proportion higher social class	-0.296

2005 Total Population - Obesity
		Covariates
	Constant	-1.638
Individual effects	20-24 years	0
	25-29 years	0.658
	30-34 years	0.658
	35-39 years	0.982
	40-44 years	0.982
	45-49 years	1.183
	50-54 years	1.183
	55-59 years	1.203
	60-64 years	1.203
	65-69 years	1.257
	70-74 years	1.257
	75+ years	0.878
	Male	-0.044
	Higher social class	-0.215
	Income Support recipient	0.168
PSU Area Effects	Proportion Asian	-0.37
	Proportion higher social class	-0.322
	Proportion living alone	-0.231
LAD area effects	Proportion higher social class	-0.266

Step 2
The fixed effects part of the model were then taken and applied to the matrix of small area covariates X held by SDRC for 100% of individuals and LADs across England, the random LAD area effect added (where it was available for an LAD), and the anti-logit applied. The probability was then summed and averaged over the LAD to produce a vector of synthetic LAD level estimates:

Yk = 1 / Nk x Sum ( anti-Logit ( Xijk B + Vk ) )

This method does not use weighting to remove bias in the parameter estimators introduced by unequal selection probabilities in the survey sampling schemes. Instead important characteristics of the sample are included in the model as covariates. The sample indicator variable S will therefore be unrelated to Y conditional on these covariates. In this case the sample can be viewed as uninformative and ignorable. There is little conflict in including theses covariates because they are, by definition, predictors of Y and so should be included in the model. If they were not, the sample design would not bias the standard estimators of the parameters.

Included in our models are measures of non-manual social classes and a 'level' for the primary sampling unit. Together these will capture, to a great extent, the unequal selection probabilities associated with the sample design. Other variables such as age will ensure that where a question or measure was taken of only a particular age group in a specific survey year that the estimates will not be biased.

Component SH2_2: Blood Pressure

Definition	Modelled estimate of proportion with high blood pressure - SBP>=160 mmHg or DBP>=95 mmHg.
Source	2001, 2001 Ethnic: Health Survey for England, 1998 to 2001, Joint Survey Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health, University College London / Department of Health (See: Health Survey for England)
	2003: Health Survey for England, 2001 to 2003, Joint Survey Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health, University College London / Department of Health (See: Health Survey for England)
	2005: Health Survey for England, 2003 to 2005, Joint Survey Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health, University College London / Department of Health (See: Health Survey for England)

Additional details

In the absence of any suitable administrative or census data, survey data was the only source of information available to construct an indicator of high blood pressure. However there are a number of problems associated with using survey data to produce Local Authority District (LAD) estimates, including small or non-existent samples in some areas leading to large variances and unstable estimates and biases introduced by particular sampling strategies.

The method used in the HPI required that a well-fitted micro level model could be identified. It also assumed that the important ways in which a group may have been over-sampled in a survey sample can be captured by covariates available in the survey and at a small area level. It involved combining all surveys available for the required year with the necessary dependent and independent variables (e.g. socio-economic status, age, gender and ethnicity). Data were gathered from the Health Survey for England (HSE) (1998 –2003) for estimates for both the whole population and for the ethnic groups.

In 1999, the focus of the HSE was the health of minority ethnic groups as a means to increase understanding through the monitoring of trends that will enable us to make predictions. For this purpose a boost sample was designed in order to yield interviews with members of the most populous six minority ethnic groups: Black Caribbean, Black African, Indian, Pakistani, Bangladeshi, Chinese, and Irish. For the purpose of this estimate, Irish is included under White, and the Black African group added (although this sample was not boosted, hence the low numbers). The table below shows the number of ethnic groups available for each year that were used in the modelling of estimates for ethnic groups:

		Year				Total
		1998	1999	2000	2001	Total
Ethnic Group	White	18019	10437	8851	17322	54629
	Black Caribbean	183	2029	143	296	2651
	Black African	143	73	98	172	486
	Indian	321	1909	203	287	2720
	Pakistani	198	2148	91	225	2662
	Bangladeshi	73	1905	64	83	2125
	Chinese	39	961	17	37	1054
Total		18796	19462	9467	18422	66327

Logit (Pijk) = Xijk B + Ujk + Vk + Eijk

2001 Total Population - Blood Pressure
		Covariates
	Constant	-5.276
Individual effects	20-24 years	0.747
	25-29 years	0.516
	30-34 years	1.388
	35-39 years	1.875
	40-44 years	2.522
	45-49 years	3.017
	50-54 years	3.491
	55-59 years	3.754
	60-64 years	4.063
	65-69 years	4.344
	70-74 years	4.710
	75+ years	4.798
	Male	0.111
	Social class I, II and IIIA	-0.099
	Income Support recipient	0.107
LAD area effects	Proportion higher social class	-0.936

2001 Ethnic Groups - Blood Pressure
		Covariates
	Constant	-5.669
Individual effects	Bangladeshi	0.058
	Black African	0.656
	Black Caribbean	0.357
	Chinese	-0.076
	Indian	0.568
	Pakistani	0.338
	20-24 years	0.738
	25-29 years	0.703
	30-34 years	1.392
	35-39 years	1.969
	40-44 years	2.641
	45-49 years	3.103
	50-54 years	3.605
	55-59 years	3.857
	60-64 years	4.21
	65-69 years	4.476
	70-74 years	4.844
	75+ years	4.953
	Male	0.125

2003 Total Population - Blood Pressure
		Covariates
	Constant	-5.950
Individual effects	20-24 years	1.404
	25-29 years	1.105
	30-34 years	2.001
	35-39 years	2.489
	40-44 years	3.144
	45-49 years	3.548
	50-54 years	4.076
	55-59 years	4.252
	60-64 years	4.438
	65-69 years	4.749
	70-74 years	5.026
	75+ years	5.308
	Male	0.092
	Higher social class	-0.121
	Income Support recipient	0.054
LAD area effects	Proportion higher social class	-0.523

2005 Total Population - Blood Pressure
		Covariates
	Constant	-6.005
Individual effects	20-24 years	0
	25-29 years	1.858
	30-34 years	1.858
	35-39 years	2.782
	40-44 years	2.782
	45-49 years	3.466
	50-54 years	3.466
	55-59 years	4.028
	60-64 years	4.028
	65-69 years	4.523
	70-74 years	4.523
	75+ years	5.075
	Male	0.017
	Higher social class	-0.02
	Income Support recipient	0.271
LAD area effects	Proportion higher social class	-0.75

Yk = 1 / Nk x Sum ( anti-Logit ( Xijk B + Vk ) )

Component SH2_3: Cholesterol

Definition	Modelled estimate of proportion with high cholesterol - if valid cholesterol result >=6.5 mmol/l
Source	2001, 2001 Ethnic: Health Survey for England, 1998 to 2001, Joint Survey Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health, University College London / Department of Health (See: Health Survey for England)
Source	2003, 2005: Health Survey for England, 2001 to 2003, Joint Survey Unit of the National Centre for Social Research and the Department of Epidemiology (See: Health Survey for England)

Additional details

In the absence of any suitable administrative or census data, survey data was the only source of information available to construct an indicator of high cholesterol. However there are a number of problems associated with using survey data to produce Local Authority District (LAD) estimates, including small or non-existent samples in some areas leading to large variances and unstable estimates and biases introduced by particular sampling strategies. The model for 2005 was not felt to be robust and therefore the 'frozen' 2003 estimates were used for 2005.

The method used in the HPI required that a well-fitted micro level model could be identified. It also assumed that the important ways in which a group may have been over-sampled in a survey sample can be captured by covariates available in the survey and at a small area level. It involved combining all surveys available for the required year with the necessary dependent and independent variables (e.g. socio-economic status, age, gender and ethnicity). Data were gathered from the Health Survey for England (HSE) (1998 –2003) for estimates for both the whole population and for the ethnic groups.

In 1999, the focus of the HSE was the health of minority ethnic groups as a means to increase understanding through the monitoring of trends that will enable us to make predictions. For this purpose a boost sample was designed in order to yield interviews with members of the most populous six minority ethnic groups: Black Caribbean, Black African, Indian, Pakistani, Bangladeshi, Chinese and Irish. For the purpose of this estimate, Irish is included under White, and the Black African group added (although this sample was not boosted, hence the low numbers). The table below shows the number of ethnic groups available for each year that were used in the modelling estimates for ethnic groups:

		Year				Total
		1998	1999	2000	2001	Total
Ethnic Group	White	18019	10437	8851	17322	54629
	Black Caribbean	183	2029	143	296	2651
	Black African	143	73	98	172	486
	Indian	321	1909	203	287	2720
	Pakistani	198	2148	91	225	2662
	Bangladeshi	73	1905	64	83	2125
	Chinese	39	961	17	37	1054
Total		18796	19462	9467	18422	66327

Only the main, adult sample, and not the oversampled ‘special populations’, was included in the modelling process. For the ethnic population estimates, the adult and 1999 ethnic minority boost was used. Cholesterol levels were derived from the blood samples taken on the nurse visit.

Logit (Pijk) = Xijk B + Ujk + Vk + Eijk

2001 Total Population - Cholesterol
		Covariates
	Constant	-3.915
Individual effects	20-24 years	0.451
	25-29 years	1.406
	30-34 years	1.862
	35-39 years	1.957
	40-44 years	2.194
	45-49 years	2.667
	50-54 years	2.955
	55-59 years	3.105
	60-64 years	3.289
	65-69 years	3.511
	70-74 years	3.529
	75+ years	3.356
	Male	-0.276
	Income Support recipient	0.147
PSU area effects	Proportion Black	-0.783

2001 Ethnic Groups - Cholesterol
		Covariates
	Constant	-3.957
Individual effects	Bangladeshi	-0.435
	Black African	-0.5
	Black Caribbean	-0.656
	Chinese	-0.69
	Indian	-0.308
	Pakistani	-0.672
	20-24 years	0.453
	25-29 years	1.488
	30-34 years	1.869
	35-39 years	2.006
	40-44 years	2.255
	45-49 years	2.626
	50-54 years	3.002
	55-59 years	3.108
	60-64 years	3.264
	65-69 years	3.474
	70-74 years	3.488
	75+ years	3.308
	Male	-0.205

2003 Total Population - Cholesterol
		Covariates
	Constant	-4.136
Individual effects	20-24 years	1.325
	25-29 years	1.747
	30-34 years	2.114
	35-39 years	2.560
	40-44 years	2.813
	45-49 years	2.991
	50-54 years	3.265
	55-59 years	3.686
	60-64 years	3.726
	65-69 years	3.702
	70-74 years	3.654
	75+ years	3.486
	Male	-0.075
	Income Support recipient	0.076

Yk = 1 / Nk x Sum ( anti-Logit ( Xijk B + Vk ) )

Component SH2_4: Low birthweight

Definition	Number of singleton live births under 2500 grams as a percentage of total live births
Source	2001, 2001 Ethnic: Annual District Birth Extract, 1999, 2000, 2001, ONS
	2003: Annual District Birth Extract, 2001, 2002, 2003, ONS
	2005: Annual District Birth Extract, 2003, 2004, 2005, ONS

Additional details

Births without a stated birth weight, extreme birth weight values of less than 500g and more than 6,000g and stillbirths have been excluded.

Further Information

All Indicators > Indicator SH2: Health capital